{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sUkJckjq8OI_"
      },
      "source": [
        "## Workspace Setup"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "dBAxJUdZPHSM"
      },
      "outputs": [],
      "source": [
        "#@title Neccessary Installs\n",
        "\n",
        "!pip install -q groq\n",
        "\n",
        "#!pip install torch\n",
        "!pip install -U accelerate\n",
        "!pip install -U bitsandbytes\n",
        "!pip install -U datasets\n",
        "!pip install -U evaluate\n",
        "!pip install -U ninja\n",
        "!pip install -U packaging\n",
        "!pip install -U peft\n",
        "!pip install -U sentencepiece\n",
        "!pip install -U transformers\n",
        "!pip install -U trl"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "m9UEQ-hmhTV-",
        "outputId": "a7faa9fe-2c3d-4b5b-d0cc-8478d627625b"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n",
            "/content/drive/MyDrive/postedBlogs/llama3RE\n"
          ]
        }
      ],
      "source": [
        "#@title Google Colab Drive Helper\n",
        "\n",
        "# For Google Colab settings\n",
        "from google.colab import userdata, drive\n",
        "\n",
        "# This will prompt for authorization\n",
        "drive.mount('/content/drive')\n",
        "\n",
        "# clone project\n",
        "! git clone https://github.com/qianniucity/llm_notebooks.git\n",
        "\n",
        "\n",
        "# Set the working directory\n",
        "%cd '/content/llm_notebooks/knowlage_graph/llama3_re'"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sjS6W3l6iTH0",
        "outputId": "c52c031b-ce02-4b58-c93c-fc6486799d85"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Token is valid (permission: write).\n",
            "Your token has been saved in your configured git credential helpers (store).\n",
            "Your token has been saved to /root/.cache/huggingface/token\n",
            "Login successful\n"
          ]
        }
      ],
      "source": [
        "#@title Hugging Face Credentials\n",
        "\n",
        "# For Hugging Face Hub setting\n",
        "from huggingface_hub import login\n",
        "\n",
        "# Upload the HuggingFace token (should have WRITE access) from Colab secrets\n",
        "HF = userdata.get('HF')\n",
        "\n",
        "# This is needed to upload the model to HuggingFace\n",
        "login(token=HF,add_to_git_credential=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "EpGhLtAi9a6i"
      },
      "outputs": [],
      "source": [
        "#@title Path Variables\n",
        "\n",
        "# Create a path variable for the data folder\n",
        "data_path = '/content/llm_notebooks/knowlage_graph/llama3_re/datas/'\n",
        "\n",
        "# SFT dataset contains extracted sentences and gold_re\n",
        "sft_data_path = f'{data_path}sft_dataset.json'\n",
        "\n",
        "# Data collected from the the mini-test\n",
        "mini_data_path = f'{data_path}mini_data.json'\n",
        "\n",
        "# Test data containing all three outputs\n",
        "all_tests_data = f'{data_path}all_tests.json'\n",
        "\n",
        "# The adjusted training dataset\n",
        "train_data_path = f'{data_path}sft_train_data.json'\n",
        "\n",
        "# Create a path variable for the SFT model to be saved locally\n",
        "sft_model_path = '/content/llm_notebooks/knowlage_graph/llama3_re/Llama3_RE/'"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JMR6rDAh3J3n"
      },
      "source": [
        "# Relation Extraction Synthetic Dataset with Llama3-70B"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ctgTF9iuGXrO"
      },
      "source": [
        "## Load & Prepare Dataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359,
          "referenced_widgets": [
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            "c84c968c6c2843a2b6d13f3371bd6c4d",
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            "bbfd96dca116486c8cda431a8b1df1bc",
            "76a5505d92894925aa171cf09b797ce6",
            "e3e0fc726f1647cf809b62390ad24315"
          ]
        },
        "id": "TYtY2ZaGhRx5",
        "outputId": "fa82fe7a-4f54-41ee-ad4e-266f10b7ee00"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "58dc9229b2e949bf8ec3ad10e5664349",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Downloading readme:   0%|          | 0.00/8.20k [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "650e64ff40354609a52dc7cdeefeae3a",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Downloading data:   0%|          | 0.00/13.1M [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "34907a9078cf452285364b1b3a65290a",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Generating train split:   0%|          | 0/15011 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "{'instruction': 'When did Virgin Australia start operating?',\n",
              " 'context': \"Virgin Australia, the trading name of Virgin Australia Airlines Pty Ltd, is an Australian-based airline. It is the largest airline by fleet size to use the Virgin brand. It commenced services on 31 August 2000 as Virgin Blue, with two aircraft on a single route. It suddenly found itself as a major airline in Australia's domestic market after the collapse of Ansett Australia in September 2001. The airline has since grown to directly serve 32 cities in Australia, from hubs in Brisbane, Melbourne and Sydney.\",\n",
              " 'response': 'Virgin Australia commenced services on 31 August 2000 as Virgin Blue, with two aircraft on a single route.',\n",
              " 'category': 'closed_qa'}"
            ]
          },
          "execution_count": 5,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#@title Load Dolly-15k Dataset\n",
        "\n",
        "from datasets import load_dataset\n",
        "\n",
        "dataset = load_dataset(\"databricks/databricks-dolly-15k\")\n",
        "\n",
        "# Display an instance\n",
        "dataset['train'][0]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "staMuvt1jBWe",
        "outputId": "e7f56b84-1439-424e-8ca8-76ade24e5bbc"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{'brainstorming',\n",
              " 'classification',\n",
              " 'closed_qa',\n",
              " 'creative_writing',\n",
              " 'general_qa',\n",
              " 'information_extraction',\n",
              " 'open_qa',\n",
              " 'summarization'}"
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#@title Determine Available Categories in Dataset\n",
        "\n",
        "dataset_categories = set([e[\"category\"] for e in dataset[\"train\"]])\n",
        "dataset_categories"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NFt6DepMjU0B",
        "outputId": "f25e68fd-55c2-49be-bade-d9585a9f93cb"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "There are 1041 instances in the dataset.\n",
            "\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "['Early in his freshman season, Ivey missed five games with a foot injury.',\n",
              " 'Lightwater is a village in the Surrey Heath district of Surrey, England, about 27 miles (43 km) southwest of central London.',\n",
              " 'The Alabama Crimson Tide football program represents the University of Alabama (variously Alabama, UA, or Bama) in the sport of American football.',\n",
              " \"Indian Railways (IR) is a statutory body under the ownership of the Ministry of Railways, Government of India that operates India's national railway system.\",\n",
              " 'Baumkuchen (German pronunciation: [ˈbaʊ̯mˌkuːxn̩] (listen)) is a kind of spit cake from German cuisine.',\n",
              " 'Aaron Fenster is a medical physicist at the University of Western Ontario Robarts Research Institute in London, Ontario, Canada.',\n",
              " 'The avocado (Persea americana) is a medium-sized, evergreen tree in the laurel family (Lauraceae).',\n",
              " 'Myron Edward \"Mike\" Ullman III (born November 26, 1946) is the former chairman and CEO of J.',\n",
              " 'On December 18, 1997, Farley was found dead by his younger brother John in his apartment in the John Hancock Center in Chicago.',\n",
              " 'Major Himalayan-origin rivers that substantially flow through India include the Ganges and the Brahmaputra, both of which drain into the Bay of Bengal.']"
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#@title Parse Data\n",
        "\n",
        "# Choose the desired category from the dataset\n",
        "ie_category = [e for e in dataset[\"train\"] if e[\"category\"]==\"information_extraction\"]\n",
        "\n",
        "# Retain only the context from each instance\n",
        "ie_context = [e[\"context\"] for e in ie_category]\n",
        "\n",
        "# Split the text into sentences (at the period) and keep the first sentence\n",
        "reduced_context = [text.split('.')[0] + '.' for text in ie_context]\n",
        "\n",
        "# Retain sequences of specified lengths only (use character length)\n",
        "sampler = [e for e in reduced_context if 30 < len(e) < 170]\n",
        "\n",
        "print(f\"There are {len(sampler)} instances in the dataset.\\n\")\n",
        "\n",
        "# Display several samples from the selected dataset\n",
        "sampler[110:120]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nGVFtKe7Hwf4"
      },
      "source": [
        "## Build the Synthetic RE Dataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "tzfzFwWpouTO"
      },
      "outputs": [],
      "source": [
        "#@title Create a System Message\n",
        "\n",
        "system_message = \"\"\"You are an experienced annontator. Extract all entities and the relations between them from the following text. Write the answer as a triple entity1|relationship|entitity2. Do not add anything else.\n",
        "Example Text: Alice is from France.\n",
        "Answer: Alice|is from|France.\n",
        "\"\"\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "67-7U_n6u3zq",
        "outputId": "2b6a56b3-10b2-4289-deaf-6b091ee7504b"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[{'role': 'system',\n",
              "  'content': 'You are an experienced annontator. Extract all entities and the relations between them from the following text. Write the answer as a triple entity1|relationship|entitity2. Do not add anything else.\\nExample Text: Alice is from France.\\nAnswer: Alice|is from|France.\\n'},\n",
              " {'role': 'user',\n",
              "  'content': 'Machine washing puts great mechanical stress on textiles, particularly natural fibers such as cotton and wool.'}]"
            ]
          },
          "execution_count": 9,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#@title Build the Messages List\n",
        "messages = [[\n",
        "    {\"role\": \"system\",\"content\": f\"{system_message}\"},\n",
        "    {\"role\": \"user\", \"content\": e}] for e in sampler]\n",
        "messages[10]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "9-kNF5UdM1x5"
      },
      "outputs": [],
      "source": [
        "#@title Instantiate Groq Client\n",
        "\n",
        "import os\n",
        "from groq import Groq\n",
        "\n",
        "gclient = Groq(\n",
        "    api_key=userdata.get(\"GROQ\"),\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "4V_I-esHalWM"
      },
      "outputs": [],
      "source": [
        "#@title Helper Functions\n",
        "\n",
        "import time\n",
        "from tqdm import tqdm\n",
        "\n",
        "def process_data(prompt):\n",
        "\n",
        "    \"\"\"Send one request and retrieve model's generation.\"\"\"\n",
        "\n",
        "    chat_completion = gclient.chat.completions.create(\n",
        "        messages=prompt, # input prompt to send to the model\n",
        "        model=\"llama3-70b-8192\", # according to GroqCloud labeling\n",
        "        temperature=0.5, # controls diversity\n",
        "        max_tokens=128, # max number tokens to generate\n",
        "        top_p=1, # proportion of likelihood weighted options to consider\n",
        "        stop=None, # string that signals to stop generating\n",
        "        stream=False, # if set partial messages are sent\n",
        "    )\n",
        "    return chat_completion.choices[0].message.content\n",
        "\n",
        "\n",
        "def send_messages(messages):\n",
        "\n",
        "    \"\"\"Process messages in batches with a pause between batches.\"\"\"\n",
        "\n",
        "    answers=[]\n",
        "    batch_size=10\n",
        "\n",
        "    for i in tqdm(range(0, len(messages), batch_size)):\n",
        "\n",
        "        batch = messages[i:i+10]  # get the next batch of messages\n",
        "\n",
        "        for message in batch:\n",
        "            output = process_data(message)\n",
        "            answers.append(output)\n",
        "\n",
        "        if i + 10 < len(messages):  # check if there are batches left\n",
        "            time.sleep(10)  # wait for 10 seconds\n",
        "\n",
        "    return answers"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3w_z7emP2C6l",
        "outputId": "620cc3c1-0992-4191-c904-49b8e1cc66fb"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "100%|██████████| 105/105 [45:27<00:00, 25.98s/it]\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "1041"
            ]
          },
          "execution_count": 12,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#@title Generate the Data\n",
        "\n",
        "answers = send_messages(messages)\n",
        "len(answers)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9lZaw7iztDax",
        "outputId": "868c73d0-cf66-4357-de56-43b1994b19a8"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{'text': 'Westworld is an American dystopian science fiction western television series created by Jonathan Nolan and Lisa Joy that first aired on October 2, 2016, on HBO.',\n",
              " 'gold_re': 'Westworld|is|American dystopian science fiction western television series.\\nWestworld|created by|Jonathan Nolan.\\nWestworld|created by|Lisa Joy.\\nWestworld|first aired on|October 2, 2016.\\nWestworld|first aired on|HBO.'}"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#@title Combine Data with Generated Dataset\n",
        "combined_dataset = [{'text': user, 'gold_re': output} for user, output in zip(sampler, answers)]\n",
        "\n",
        "# Print the combined list to check\n",
        "combined_dataset[22]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "RM5hwi9-tfBU"
      },
      "outputs": [],
      "source": [
        "#@title Save the Combined Dataset\n",
        "\n",
        "import json\n",
        "\n",
        "with open(sft_data_path, 'w') as file:\n",
        "    json.dump(combined_dataset, file)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iIhgi6krQf8A"
      },
      "source": [
        "# Evaluate Llama3-8B on Relation Extraction Task"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zF_ubOegcZnN",
        "outputId": "2b4d05ac-6762-42b5-f43c-cd27957bd858"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[{'role': 'system',\n",
              "  'content': 'You are an experienced annontator. Extract all entities and the relations between them from the following text. Write the answer as a triple entity1|relationship|entitity2. Do not add anything else.\\nExample Text: Alice is from France.\\nAnswer: Alice|is from|France.\\n'},\n",
              " {'role': 'user',\n",
              "  'content': \"lot\\nWhilst waiting for his dinner at Pleasant's Coffee House, Hercule Poirot meets a young woman named Jennie.\"}]"
            ]
          },
          "execution_count": 15,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#@title Build a Samples Dataset\n",
        "\n",
        "import random\n",
        "random.seed(17)\n",
        "\n",
        "# Select 20 random entries\n",
        "mini_data = random.sample(combined_dataset, 20)\n",
        "\n",
        "# Build conversational format\n",
        "parsed_mini_data = [[{'role': 'system', 'content': system_message},\n",
        "                     {'role': 'user', 'content': e['text']}] for e in mini_data]\n",
        "\n",
        "parsed_mini_data[1]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bO-BOul4jdQJ",
        "outputId": "c6350139-4d4e-4b3a-e56b-1039f13a3d29"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "1017"
            ]
          },
          "execution_count": 16,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#@title Create a Training Set for FineTuning\n",
        "\n",
        "train_data = [item for item in combined_dataset if item not in mini_data]\n",
        "len(train_data)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "940fONzPbvg4"
      },
      "outputs": [],
      "source": [
        "#@title Helper Function\n",
        "\n",
        "def process_data(prompt):\n",
        "\n",
        "    \"\"\"Send one request and retrieve model's generation.\"\"\"\n",
        "\n",
        "    chat_completion = gclient.chat.completions.create(\n",
        "        messages=prompt, # input prompt to send to the model\n",
        "        model=\"llama3-8b-8192\", # according to GroqCloud labeling\n",
        "        temperature=0.5, # controls diversity\n",
        "        max_tokens=128, # max number tokens to generate\n",
        "        top_p=1, # proportion of likelihood weighted options to consider\n",
        "        stop=None, # string that signals to stop generating\n",
        "        stream=False, # if set partial messages are sent\n",
        "    )\n",
        "    return chat_completion.choices[0].message.content"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        },
        "id": "HJwsY0KBdRdv",
        "outputId": "d26dd219-7581-4f03-d58d-eb5b0634d3ef"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'Indonesia|is|Republic of Indonesia.\\nIndonesia|is located in|Southeast Asia.\\nIndonesia|is located in|Oceania.\\nIndonesia|is between|Indian.\\nIndonesia|is between|Pacific.\\nRepublic of Indonesia|is officially|Indonesia.\\nSoutheast Asia|is located in|Indonesia.\\nOceania|is located in|Indonesia.\\nIndian|is|ocean.\\nPacific|is|ocean.'"
            ]
          },
          "execution_count": 18,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#@title Perform RE on Samples Data with Llama-8B\n",
        "\n",
        "outputs = []\n",
        "for message in parsed_mini_data:\n",
        "    output = process_data(message)\n",
        "    outputs.append(output)\n",
        "\n",
        "outputs[3]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IouW6aygbty3",
        "outputId": "9cca0f0c-ee23-4756-9935-f891e8583ac9"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{'text': 'Long before any knowledge of electricity existed, people were aware of shocks from electric fish.',\n",
              " 'gold_re': 'people|were aware of|shocks\\nshocks|from|electric fish',\n",
              " 'test_re': 'Electric fish|were known to give|people.'}"
            ]
          },
          "execution_count": 19,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#@title Combine the Samples Data with Generated RE Data\n",
        "\n",
        "# Adding new key 'test_re' with values from the list\n",
        "for i, dct in enumerate(mini_data):\n",
        "    dct['test_re'] = outputs[i]\n",
        "\n",
        "mini_data[2]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "68yc-vg7gMEW",
        "outputId": "c8c32143-1ed1-45c2-a68c-8605cb12aa2f"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 20,\n  \"fields\": [\n    {\n      \"column\": \"text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 20,\n        \"samples\": [\n          \"There were two teams relegated last season to the 2023 J2 League.\",\n          \"California is a state in the Western United States, located along the Pacific Coast.\",\n          \"Zeus (\\u0396\\u03b5\\u03cd\\u03c2, Ze\\u00fas)\\n\\nKing of the gods, ruler of Mount Olympus, and god of the sky, weather, thunder, lightning, law, order, and justice.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"gold_re\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 20,\n        \"samples\": [\n          \"2023 J2 League|will have|two teams.\\ntwo teams|were relegated to|2023 J2 League.\\nlast season|saw relegation of|two teams.\",\n          \"California|is a|state.\\nCalifornia|is located in|Western United States.\\nCalifornia|is located along|Pacific Coast.\\nWestern United States|is in|United States.\\nPacific Coast|is in|United States.\",\n          \"Zeus|is|King of the gods\\nZeus|is|ruler of|Mount Olympus\\nZeus|is|god of|sky\\nZeus|is|god of|weather\\nZeus|is|god of|thunder\\nZeus|is|god of|lightning\\nZeus|is|god of|law\\nZeus|is|god of|order\\nZeus|is|god of|justice\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"test_re\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 20,\n        \"samples\": [\n          \"Team A|was relegated to|2023 J2 League\\nTeam B|was relegated to|2023 J2 League\",\n          \"California|is a|state\\nCalifornia|is located|Pacific Coast\\nCalifornia|is located|United States\\nUnited States|is a|country\",\n          \"Zeus|is the king of|gods.\\nZeus|is the ruler of|Mount Olympus.\\nZeus|is the god of|sky.\\nZeus|is the god of|weather.\\nZeus|is the god of|thunder.\\nZeus|is the god of|lightning.\\nZeus|is the god of|law.\\nZeus|is the god of|order.\\nZeus|is the god of|justice.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
              "type": "dataframe",
              "variable_name": "df"
            },
            "text/html": [
              "\n",
              "  <div id=\"df-d73dd781-bf9b-42f0-9923-a6dd9c4be175\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>text</th>\n",
              "      <th>gold_re</th>\n",
              "      <th>test_re</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>There were two teams relegated last season to the 2023 J2 League.</td>\n",
              "      <td>2023 J2 League|will have|two teams.\\ntwo teams|were relegated to|2023 J2 League.\\nlast season|saw relegation of|two teams.</td>\n",
              "      <td>Team A|was relegated to|2023 J2 League\\nTeam B|was relegated to|2023 J2 League</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>lot\\nWhilst waiting for his dinner at Pleasant's Coffee House, Hercule Poirot meets a young woman named Jennie.</td>\n",
              "      <td>Hercule Poirot|meets|Jennie.\\nHercule Poirot|waits for|dinner.\\nHercule Poirot|is at|Pleasant's Coffee House.\\nJennie|is met by|Hercule Poirot.\\nJennie|is a|young woman.</td>\n",
              "      <td>Hercule Poirot|meets|Jennie.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Long before any knowledge of electricity existed, people were aware of shocks from electric fish.</td>\n",
              "      <td>people|were aware of|shocks\\nshocks|from|electric fish</td>\n",
              "      <td>Electric fish|were known to give|people.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Indonesia, officially the Republic of Indonesia, is a country in Southeast Asia and Oceania between the Indian and Pacific oceans.</td>\n",
              "      <td>Indonesia|is a country in|Southeast Asia.\\nIndonesia|is a country in|Oceania.\\nIndonesia|is between|Indian ocean.\\nIndonesia|is between|Pacific ocean.\\nRepublic of Indonesia|is officially known as|Indonesia.</td>\n",
              "      <td>Indonesia|is|Republic of Indonesia.\\nIndonesia|is located in|Southeast Asia.\\nIndonesia|is located in|Oceania.\\nIndonesia|is between|Indian.\\nIndonesia|is between|Pacific.\\nRepublic of Indonesia|is officially|Indonesia.\\nSoutheast Asia|is located in|Indonesia.\\nOceania|is located in|Indonesia.\\nIndian|is|ocean.\\nPacific|is|ocean.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>In 1982, Nintendo developed a prototype system called the Advanced Video System (AVS).</td>\n",
              "      <td>Nintendo|developed|Advanced Video System (AVS).\\nNintendo|developed|prototype system.\\nAdvanced Video System (AVS)|is|prototype system.</td>\n",
              "      <td>Nintendo|developed|Advanced Video System</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Bloomington is a city in and the county seat of Monroe County, Indiana, United States.</td>\n",
              "      <td>Bloomington|is in|Monroe County.\\nBloomington|is in|Indiana.\\nBloomington|is in|United States.\\nBloomington|is|city.\\nBloomington|is|county seat.\\nMonroe County|is in|Indiana.\\nMonroe County|is in|United States.</td>\n",
              "      <td>Bloomington|is a|city\\nBloomington|is|county seat\\nBloomington|is in|Monroe County\\nBloomington|is in|Indiana\\nBloomington|is in|United States\\nMonroe County|is|location\\nIndiana|is|location\\nUnited States|is|location</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>The Texas barrier islands are a chain of barrier islands in the Gulf of Mexico along the Texas Gulf Coast.</td>\n",
              "      <td>Texas barrier islands|are a chain of|barrier islands.\\nTexas barrier islands|are in the|Gulf of Mexico.\\nTexas barrier islands|are along the|Texas Gulf Coast.</td>\n",
              "      <td>Texas|is|barrier islands, Texas|is|chain, Texas|is|barrier islands|of, barrier islands|are|chain, barrier islands|are|in, barrier islands|are|along, Gulf of Mexico|is|in, Texas Gulf Coast|is|along.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Johnson was rated among the nation's top 10 wide receivers and top 100 players by virtually every recruiting analyst.</td>\n",
              "      <td>Johnson|was rated among|the nation's top 10 wide receivers.\\nJohnson|was rated among|the nation's top 100 players.</td>\n",
              "      <td>Johnson|was rated|nation's\\nJohnson|was rated|top\\nJohnson|was rated|wide receivers\\nJohnson|was rated|top 10\\nJohnson|was rated|100\\nJohnson|was rated|players\\nanalyst|rated|Johnson</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>The geologic time scale is a way of representing deep time based on events that have occurred throughout Earth's history, a time span of about 4.</td>\n",
              "      <td>geologic time scale|is a way of representing|deep time.\\ndeep time|is based on|events.\\nevents|have occurred throughout|Earth's history.\\nEarth's history|has a time span of|4.</td>\n",
              "      <td>The geologic time scale|is based on|events that have occurred throughout Earth's history, Earth's history|is part of|The geologic time scale, The geologic time scale|represents|deep time, deep time|is represented by|The geologic time scale, The geologic time scale|is based on|a time span of about 4.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Titanic is a 1997 American epic romance and disaster film directed, written, produced, and co-edited by James Cameron.</td>\n",
              "      <td>Titanic|is|film.\\nTitanic|was directed by|James Cameron.\\nTitanic|was written by|James Cameron.\\nTitanic|was produced by|James Cameron.\\nTitanic|was co-edited by|James Cameron.\\nJames Cameron|directed|Titanic.\\nJames Cameron|wrote|Titanic.\\nJames Cameron|produced|Titanic.\\nJames Cameron|co-edited|Titanic.\\nTitanic|is|American epic romance and disaster film.</td>\n",
              "      <td>Titanic|is a|1997 American epic romance and disaster film\\nTitanic|is directed by|James Cameron\\nTitanic|is written by|James Cameron\\nTitanic|is produced by|James Cameron\\nTitanic|is co-edited by|James Cameron</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Most avalanches occur spontaneously during storms under increased load due to snowfall and/or erosion.</td>\n",
              "      <td>avalanches|occur|storms\\nstorms|have|snowfall\\nstorms|have|erosion\\navalanches|occur under|load\\nload|is increased due to|snowfall\\nload|is increased due to|erosion</td>\n",
              "      <td>Avalanches|occur spontaneously|storms.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Several species of shrub of the genus Coffea produce the berries from which coffee is extracted.</td>\n",
              "      <td>Coffea|is genus of|shrubs.\\nshrubs|produce|berries.\\nberries|are source of|coffee.</td>\n",
              "      <td>Coffea|produce|berries.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>The Flash (Bartholomew Henry \"Barry\" Allen) is a superhero appearing in American comic books published by DC Comics.</td>\n",
              "      <td>The Flash|is|Bartholomew Henry \"Barry\" Allen.\\nThe Flash|appears in|American comic books.\\nAmerican comic books|are published by|DC Comics.</td>\n",
              "      <td>The Flash|is|DC Comics.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Electricity generation is the process of generating electric power from sources of primary energy.</td>\n",
              "      <td>Electricity generation|is the process of generating|electric power.\\nElectricity generation|is the process of generating|primary energy.</td>\n",
              "      <td>Electricity generation|is the process of|primary energy.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Angelo Moriondo, from Turin, is often erroneously credited for inventing the beverage, since he patented a steam-driven coffee beverage making device in 1884 (No.</td>\n",
              "      <td>Angelo Moriondo|is from|Turin.\\nAngelo Moriondo|patented|steam-driven coffee beverage making device.\\nAngelo Moriondo|invented in|1884.</td>\n",
              "      <td>Angelo Moriondo|is from|Turin.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Zeus (Ζεύς, Zeús)\\n\\nKing of the gods, ruler of Mount Olympus, and god of the sky, weather, thunder, lightning, law, order, and justice.</td>\n",
              "      <td>Zeus|is|King of the gods\\nZeus|is|ruler of|Mount Olympus\\nZeus|is|god of|sky\\nZeus|is|god of|weather\\nZeus|is|god of|thunder\\nZeus|is|god of|lightning\\nZeus|is|god of|law\\nZeus|is|god of|order\\nZeus|is|god of|justice</td>\n",
              "      <td>Zeus|is the king of|gods.\\nZeus|is the ruler of|Mount Olympus.\\nZeus|is the god of|sky.\\nZeus|is the god of|weather.\\nZeus|is the god of|thunder.\\nZeus|is the god of|lightning.\\nZeus|is the god of|law.\\nZeus|is the god of|order.\\nZeus|is the god of|justice.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>In probability theory and statistics, the harmonic distribution is a continuous probability distribution.</td>\n",
              "      <td>probability theory|is in|statistics.\\nharmonic distribution|is a|continuous probability distribution.\\nprobability theory|deals with|harmonic distribution.</td>\n",
              "      <td>Harmonic distribution|is a|continuous probability distribution.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>California is a state in the Western United States, located along the Pacific Coast.</td>\n",
              "      <td>California|is a|state.\\nCalifornia|is located in|Western United States.\\nCalifornia|is located along|Pacific Coast.\\nWestern United States|is in|United States.\\nPacific Coast|is in|United States.</td>\n",
              "      <td>California|is a|state\\nCalifornia|is located|Pacific Coast\\nCalifornia|is located|United States\\nUnited States|is a|country</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Atlantis Princess is the third Korean-language studio album by South Korean singer BoA, released on May 30, 2003 by SM Entertainment.</td>\n",
              "      <td>Atlantis Princess|is the third Korean-language studio album of|BoA.\\nBoA|is|South Korean singer.\\nAtlantis Princess|was released on|May 30, 2003.\\nAtlantis Princess|was released by|SM Entertainment.</td>\n",
              "      <td>BoA|is the artist of|Atlantis Princess\\nBoA|is released by|SM Entertainment\\nBoA|is from|South Korea\\nAtlantis Princess|is released by|SM Entertainment\\nAtlantis Princess|is released on|May 30, 2003\\nAtlantis Princess|is the third Korean-language studio album by|BoA\\nSM Entertainment|is the publisher of|Atlantis Princess</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Seattle (/siˈætəl/ (listen) see-AT-əl) is a seaport city on the West Coast of the United States.</td>\n",
              "      <td>Seattle|is a|seaport city.\\nSeattle|is located on the|West Coast.\\nSeattle|is located in the|United States.</td>\n",
              "      <td>Seattle|is|United States.\\nSeattle|is located on|West Coast.\\nSeattle|is a|seaport city.</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d73dd781-bf9b-42f0-9923-a6dd9c4be175')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-d73dd781-bf9b-42f0-9923-a6dd9c4be175 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-d73dd781-bf9b-42f0-9923-a6dd9c4be175');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-cea646cf-130b-4c38-8c1d-8ab630d2051f\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-cea646cf-130b-4c38-8c1d-8ab630d2051f')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-cea646cf-130b-4c38-8c1d-8ab630d2051f button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_3bb3fd6b-3966-400f-825b-69a843ba39f5\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_3bb3fd6b-3966-400f-825b-69a843ba39f5 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "                                                                                                                                                                  text  \\\n",
              "0                                                                                                    There were two teams relegated last season to the 2023 J2 League.   \n",
              "1                                                      lot\\nWhilst waiting for his dinner at Pleasant's Coffee House, Hercule Poirot meets a young woman named Jennie.   \n",
              "2                                                                    Long before any knowledge of electricity existed, people were aware of shocks from electric fish.   \n",
              "3                                   Indonesia, officially the Republic of Indonesia, is a country in Southeast Asia and Oceania between the Indian and Pacific oceans.   \n",
              "4                                                                               In 1982, Nintendo developed a prototype system called the Advanced Video System (AVS).   \n",
              "5                                                                               Bloomington is a city in and the county seat of Monroe County, Indiana, United States.   \n",
              "6                                                           The Texas barrier islands are a chain of barrier islands in the Gulf of Mexico along the Texas Gulf Coast.   \n",
              "7                                                Johnson was rated among the nation's top 10 wide receivers and top 100 players by virtually every recruiting analyst.   \n",
              "8                    The geologic time scale is a way of representing deep time based on events that have occurred throughout Earth's history, a time span of about 4.   \n",
              "9                                               Titanic is a 1997 American epic romance and disaster film directed, written, produced, and co-edited by James Cameron.   \n",
              "10                                                              Most avalanches occur spontaneously during storms under increased load due to snowfall and/or erosion.   \n",
              "11                                                                    Several species of shrub of the genus Coffea produce the berries from which coffee is extracted.   \n",
              "12                                                The Flash (Bartholomew Henry \"Barry\" Allen) is a superhero appearing in American comic books published by DC Comics.   \n",
              "13                                                                  Electricity generation is the process of generating electric power from sources of primary energy.   \n",
              "14  Angelo Moriondo, from Turin, is often erroneously credited for inventing the beverage, since he patented a steam-driven coffee beverage making device in 1884 (No.   \n",
              "15                            Zeus (Ζεύς, Zeús)\\n\\nKing of the gods, ruler of Mount Olympus, and god of the sky, weather, thunder, lightning, law, order, and justice.   \n",
              "16                                                           In probability theory and statistics, the harmonic distribution is a continuous probability distribution.   \n",
              "17                                                                                California is a state in the Western United States, located along the Pacific Coast.   \n",
              "18                               Atlantis Princess is the third Korean-language studio album by South Korean singer BoA, released on May 30, 2003 by SM Entertainment.   \n",
              "19                                                                    Seattle (/siˈætəl/ (listen) see-AT-əl) is a seaport city on the West Coast of the United States.   \n",
              "\n",
              "                                                                                                                                                                                                                                                                                                                                                                    gold_re  \\\n",
              "0                                                                                                                                                                                                                                                2023 J2 League|will have|two teams.\\ntwo teams|were relegated to|2023 J2 League.\\nlast season|saw relegation of|two teams.   \n",
              "1                                                                                                                                                                                                 Hercule Poirot|meets|Jennie.\\nHercule Poirot|waits for|dinner.\\nHercule Poirot|is at|Pleasant's Coffee House.\\nJennie|is met by|Hercule Poirot.\\nJennie|is a|young woman.   \n",
              "2                                                                                                                                                                                                                                                                                                                    people|were aware of|shocks\\nshocks|from|electric fish   \n",
              "3                                                                                                                                                           Indonesia|is a country in|Southeast Asia.\\nIndonesia|is a country in|Oceania.\\nIndonesia|is between|Indian ocean.\\nIndonesia|is between|Pacific ocean.\\nRepublic of Indonesia|is officially known as|Indonesia.   \n",
              "4                                                                                                                                                                                                                                   Nintendo|developed|Advanced Video System (AVS).\\nNintendo|developed|prototype system.\\nAdvanced Video System (AVS)|is|prototype system.   \n",
              "5                                                                                                                                                       Bloomington|is in|Monroe County.\\nBloomington|is in|Indiana.\\nBloomington|is in|United States.\\nBloomington|is|city.\\nBloomington|is|county seat.\\nMonroe County|is in|Indiana.\\nMonroe County|is in|United States.   \n",
              "6                                                                                                                                                                                                            Texas barrier islands|are a chain of|barrier islands.\\nTexas barrier islands|are in the|Gulf of Mexico.\\nTexas barrier islands|are along the|Texas Gulf Coast.   \n",
              "7                                                                                                                                                                                                                                                        Johnson|was rated among|the nation's top 10 wide receivers.\\nJohnson|was rated among|the nation's top 100 players.   \n",
              "8                                                                                                                                                                                           geologic time scale|is a way of representing|deep time.\\ndeep time|is based on|events.\\nevents|have occurred throughout|Earth's history.\\nEarth's history|has a time span of|4.   \n",
              "9   Titanic|is|film.\\nTitanic|was directed by|James Cameron.\\nTitanic|was written by|James Cameron.\\nTitanic|was produced by|James Cameron.\\nTitanic|was co-edited by|James Cameron.\\nJames Cameron|directed|Titanic.\\nJames Cameron|wrote|Titanic.\\nJames Cameron|produced|Titanic.\\nJames Cameron|co-edited|Titanic.\\nTitanic|is|American epic romance and disaster film.   \n",
              "10                                                                                                                                                                                                     avalanches|occur|storms\\nstorms|have|snowfall\\nstorms|have|erosion\\navalanches|occur under|load\\nload|is increased due to|snowfall\\nload|is increased due to|erosion   \n",
              "11                                                                                                                                                                                                                                                                                       Coffea|is genus of|shrubs.\\nshrubs|produce|berries.\\nberries|are source of|coffee.   \n",
              "12                                                                                                                                                                                                                              The Flash|is|Bartholomew Henry \"Barry\" Allen.\\nThe Flash|appears in|American comic books.\\nAmerican comic books|are published by|DC Comics.   \n",
              "13                                                                                                                                                                                                                                 Electricity generation|is the process of generating|electric power.\\nElectricity generation|is the process of generating|primary energy.   \n",
              "14                                                                                                                                                                                                                                  Angelo Moriondo|is from|Turin.\\nAngelo Moriondo|patented|steam-driven coffee beverage making device.\\nAngelo Moriondo|invented in|1884.   \n",
              "15                                                                                                                                                 Zeus|is|King of the gods\\nZeus|is|ruler of|Mount Olympus\\nZeus|is|god of|sky\\nZeus|is|god of|weather\\nZeus|is|god of|thunder\\nZeus|is|god of|lightning\\nZeus|is|god of|law\\nZeus|is|god of|order\\nZeus|is|god of|justice   \n",
              "16                                                                                                                                                                                                              probability theory|is in|statistics.\\nharmonic distribution|is a|continuous probability distribution.\\nprobability theory|deals with|harmonic distribution.   \n",
              "17                                                                                                                                                                      California|is a|state.\\nCalifornia|is located in|Western United States.\\nCalifornia|is located along|Pacific Coast.\\nWestern United States|is in|United States.\\nPacific Coast|is in|United States.   \n",
              "18                                                                                                                                                                   Atlantis Princess|is the third Korean-language studio album of|BoA.\\nBoA|is|South Korean singer.\\nAtlantis Princess|was released on|May 30, 2003.\\nAtlantis Princess|was released by|SM Entertainment.   \n",
              "19                                                                                                                                                                                                                                                              Seattle|is a|seaport city.\\nSeattle|is located on the|West Coast.\\nSeattle|is located in the|United States.   \n",
              "\n",
              "                                                                                                                                                                                                                                                                                                                                        test_re  \n",
              "0                                                                                                                                                                                                                                                                Team A|was relegated to|2023 J2 League\\nTeam B|was relegated to|2023 J2 League  \n",
              "1                                                                                                                                                                                                                                                                                                                  Hercule Poirot|meets|Jennie.  \n",
              "2                                                                                                                                                                                                                                                                                                      Electric fish|were known to give|people.  \n",
              "3   Indonesia|is|Republic of Indonesia.\\nIndonesia|is located in|Southeast Asia.\\nIndonesia|is located in|Oceania.\\nIndonesia|is between|Indian.\\nIndonesia|is between|Pacific.\\nRepublic of Indonesia|is officially|Indonesia.\\nSoutheast Asia|is located in|Indonesia.\\nOceania|is located in|Indonesia.\\nIndian|is|ocean.\\nPacific|is|ocean.  \n",
              "4                                                                                                                                                                                                                                                                                                      Nintendo|developed|Advanced Video System  \n",
              "5                                                                                                                     Bloomington|is a|city\\nBloomington|is|county seat\\nBloomington|is in|Monroe County\\nBloomington|is in|Indiana\\nBloomington|is in|United States\\nMonroe County|is|location\\nIndiana|is|location\\nUnited States|is|location  \n",
              "6                                                                                                                                         Texas|is|barrier islands, Texas|is|chain, Texas|is|barrier islands|of, barrier islands|are|chain, barrier islands|are|in, barrier islands|are|along, Gulf of Mexico|is|in, Texas Gulf Coast|is|along.  \n",
              "7                                                                                                                                                        Johnson|was rated|nation's\\nJohnson|was rated|top\\nJohnson|was rated|wide receivers\\nJohnson|was rated|top 10\\nJohnson|was rated|100\\nJohnson|was rated|players\\nanalyst|rated|Johnson  \n",
              "8                                  The geologic time scale|is based on|events that have occurred throughout Earth's history, Earth's history|is part of|The geologic time scale, The geologic time scale|represents|deep time, deep time|is represented by|The geologic time scale, The geologic time scale|is based on|a time span of about 4.  \n",
              "9                                                                                                                             Titanic|is a|1997 American epic romance and disaster film\\nTitanic|is directed by|James Cameron\\nTitanic|is written by|James Cameron\\nTitanic|is produced by|James Cameron\\nTitanic|is co-edited by|James Cameron  \n",
              "10                                                                                                                                                                                                                                                                                                       Avalanches|occur spontaneously|storms.  \n",
              "11                                                                                                                                                                                                                                                                                                                      Coffea|produce|berries.  \n",
              "12                                                                                                                                                                                                                                                                                                                      The Flash|is|DC Comics.  \n",
              "13                                                                                                                                                                                                                                                                                     Electricity generation|is the process of|primary energy.  \n",
              "14                                                                                                                                                                                                                                                                                                               Angelo Moriondo|is from|Turin.  \n",
              "15                                                                            Zeus|is the king of|gods.\\nZeus|is the ruler of|Mount Olympus.\\nZeus|is the god of|sky.\\nZeus|is the god of|weather.\\nZeus|is the god of|thunder.\\nZeus|is the god of|lightning.\\nZeus|is the god of|law.\\nZeus|is the god of|order.\\nZeus|is the god of|justice.  \n",
              "16                                                                                                                                                                                                                                                                              Harmonic distribution|is a|continuous probability distribution.  \n",
              "17                                                                                                                                                                                                                  California|is a|state\\nCalifornia|is located|Pacific Coast\\nCalifornia|is located|United States\\nUnited States|is a|country  \n",
              "18           BoA|is the artist of|Atlantis Princess\\nBoA|is released by|SM Entertainment\\nBoA|is from|South Korea\\nAtlantis Princess|is released by|SM Entertainment\\nAtlantis Princess|is released on|May 30, 2003\\nAtlantis Princess|is the third Korean-language studio album by|BoA\\nSM Entertainment|is the publisher of|Atlantis Princess  \n",
              "19                                                                                                                                                                                                                                                     Seattle|is|United States.\\nSeattle|is located on|West Coast.\\nSeattle|is a|seaport city.  "
            ]
          },
          "execution_count": 20,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#@title Display Llama3 70B and 8B RE Outputs on Samples\n",
        "\n",
        "import pandas as pd\n",
        "pd.set_option('display.max_colwidth', None)\n",
        "\n",
        "# Create a dataframe from collected data\n",
        "df = pd.DataFrame(mini_data)\n",
        "df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "MHwLD5ukj6T3"
      },
      "outputs": [],
      "source": [
        "#@title Save the Datasets\n",
        "\n",
        "import json\n",
        "\n",
        "# Data collected from the mini-test\n",
        "with open(mini_data_path, 'w') as file:\n",
        "    json.dump(mini_data, file)\n",
        "\n",
        "# The adjusted training dataset\n",
        "with open(train_data_path, 'w') as file:\n",
        "    json.dump(train_data, file)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4niI_IHyk88V"
      },
      "source": [
        "# Supervised Fine-Tuning Llama3-8B"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SJCLzh5kl884",
        "outputId": "2e48237b-f897-4ef1-bc20-c88525d0a547"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "The PyTorch version is 2.2.1+cu121.\n",
            "Datasets version is 2.19.0.\n",
            "Transformers version is 4.40.1.\n",
            "TRL version is 0.8.6.\n"
          ]
        }
      ],
      "source": [
        "#@title Display Libraries Versions\n",
        "\n",
        "import torch\n",
        "import datasets\n",
        "import transformers\n",
        "import trl\n",
        "\n",
        "print(f\"The PyTorch version is {torch.__version__}.\")\n",
        "print(f\"Datasets version is {datasets.__version__}.\")\n",
        "print(f\"Transformers version is {transformers.__version__}.\")\n",
        "print(f\"TRL version is {trl.__version__}.\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6njW4Nnd3IlQ",
        "outputId": "73b338be-7f94-4692-ac06-1fcf121e5757"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Cuda major version: 8.\n",
            "Cuda minor version: 0\n",
            "env: MAX_JOBS=2 # for Google Colab\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.5/2.5 MB\u001b[0m \u001b[31m35.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m44.6/44.6 kB\u001b[0m \u001b[31m6.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Building wheel for flash-attn (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "torch_dtype = torch.bfloat16\n",
            "attn_implementation = flash_attention_2\n"
          ]
        }
      ],
      "source": [
        "#@title Assert Cuda Capabilities for Flash Attention\n",
        "\n",
        "# Assert Cuda Capability for Flash Attention\n",
        "major_version, minor_version = torch.cuda.get_device_capability()\n",
        "print(f\"Cuda major version: {major_version}.\\nCuda minor version: {minor_version}\")\n",
        "\n",
        "# adapted from: https://github.com/mlabonne/llm-course\n",
        "if torch.cuda.get_device_capability()[0] >= 8:\n",
        "    # Limit the number of jobs to accomodate the compute capabilities\n",
        "    %env MAX_JOBS=2 # for Google Colab\n",
        "\n",
        "    # Install flash attention - for Ampere GPUs\n",
        "    %pip install flash-attn -q --no-build-isolation\n",
        "\n",
        "    torch_dtype = torch.bfloat16\n",
        "    attn_implementation = \"flash_attention_2\"\n",
        "\n",
        "else:\n",
        "    torch_dtype = torch.float16\n",
        "    attn_implementation = \"eager\"\n",
        "\n",
        "print(f\"torch_dtype = {torch_dtype}\")\n",
        "print(f\"attn_implementation = {attn_implementation}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ue9ckYIfmKr8",
        "outputId": "fe4ff460-0b49-41ea-d1fd-fb7b35213f90"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "GPU = NVIDIA A100-SXM4-40GB. Max memory = 39.564 GB.\n",
            "0.0 GB of memory reserved.\n"
          ]
        }
      ],
      "source": [
        "#@title Resources Estimation\n",
        "gpu_stats = torch.cuda.get_device_properties(0)\n",
        "start_gpu_memory = round(torch.cuda.max_memory_reserved() / 1024 / 1024 / 1024, 3)\n",
        "max_memory = round(gpu_stats.total_memory / 1024 / 1024 / 1024, 3)\n",
        "print(f\"GPU = {gpu_stats.name}. Max memory = {max_memory} GB.\")\n",
        "print(f\"{start_gpu_memory} GB of memory reserved.\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ZIQjxJHNnYvl"
      },
      "outputs": [],
      "source": [
        "#@title LLM Model Name\n",
        "\n",
        "model_id  =  \"meta-llama/Meta-Llama-3-8B\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QEv4Lgk3EV4d"
      },
      "source": [
        "## Prepare the SFT Dataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0a-BpuiJn0Nd",
        "outputId": "866c5982-d81d-4968-9995-21624340c237"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{'text': 'Another Hindu term that is sometimes translated as deity is Ishvara, or alternatively various deities are described, state Sorajjakool et al.',\n",
              " 'gold_re': 'Ishvara|is|deity.\\nSorajjakool et al.|state| \\ndeities|are described|'}"
            ]
          },
          "execution_count": 26,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#@title Load the SFT Dataset\n",
        "import json\n",
        "\n",
        "with open(train_data_path, 'rb') as f:\n",
        "\ttrain_data = json.load(f)\n",
        "\n",
        "train_data[123]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Pqavxi0I0Cxf"
      },
      "outputs": [],
      "source": [
        "#@title Function to Parse to Conversational Format\n",
        "\n",
        "# Create the System Message\n",
        "\n",
        "system_message = \"\"\"You are an experienced annontator. Extract all entities and the relations between them from the following text. Write the answer as a triple entity1|relationship|entitity2. Do not add anything else.\n",
        "Example Text: Alice is from France.\n",
        "Answer: Alice|is from|France.\n",
        "\"\"\"\n",
        "\n",
        "def create_conversation(sample):\n",
        "    return {\n",
        "        \"messages\": [\n",
        "            {\"role\": \"system\",\"content\": system_message},\n",
        "            {\"role\": \"user\", \"content\": sample[\"text\"]},\n",
        "            {\"role\": \"assistant\", \"content\": sample[\"gold_re\"]}\n",
        "        ]\n",
        "    }\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 118,
          "referenced_widgets": [
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            "30709df87e994398aab623f473112025",
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            "3f514f23d1a746e2a406ae0085b92bf9",
            "e4408301317b40da9dd5c13a396b55d1",
            "a232cdea46ef4a6aaaab14c5805eda89",
            "7da520b98c684597bc41f82929c6dbd1"
          ]
        },
        "id": "By4hTZimrgpx",
        "outputId": "bf2f1d4a-d43f-4406-cb48-2a6db797ed0e"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "aa9b58a641e549e8a28ae5273b9f086f",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Map:   0%|          | 0/1017 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Dataset({\n",
            "    features: ['messages'],\n",
            "    num_rows: 1017\n",
            "})\n"
          ]
        }
      ],
      "source": [
        "#@title Convert Data to HuggingFace Format\n",
        "\n",
        "from datasets import load_dataset, Dataset\n",
        "\n",
        "train_dataset = Dataset.from_list(train_data)\n",
        "\n",
        "# Transform to conversational format\n",
        "train_dataset = train_dataset.map(create_conversation,\n",
        "                      remove_columns=train_dataset.features,\n",
        "                      batched=False)\n",
        "print(train_dataset)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UoydSzvA06W9",
        "outputId": "f50fcbe1-1b96-4793-e338-3ecff80f49fb"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[{'content': 'You are an experienced annontator. Extract all entities and the relations between them from the following text. Write the answer as a triple entity1|relationship|entitity2. Do not add anything else.\\nExample Text: Alice is from France.\\nAnswer: Alice|is from|France.\\n',\n",
              "  'role': 'system'},\n",
              " {'content': 'Another Hindu term that is sometimes translated as deity is Ishvara, or alternatively various deities are described, state Sorajjakool et al.',\n",
              "  'role': 'user'},\n",
              " {'content': 'Ishvara|is|deity.\\nSorajjakool et al.|state| \\ndeities|are described|',\n",
              "  'role': 'assistant'}]"
            ]
          },
          "execution_count": 29,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#@title Display a Sample\n",
        "train_dataset[\"messages\"][123]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zipOr9nvg901"
      },
      "source": [
        "## Tokenizer and Chat Template"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 130,
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            "e82f3c81a6764759a08a97d1981e0e75",
            "8c1a8a8c81824e83ac2be8e759ee4338"
          ]
        },
        "id": "56cKo54whJCk",
        "outputId": "937a3383-fb7d-43f0-811a-448b535ab402"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "4fef43bc830a4efca256fbc1e783f1d1",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "tokenizer_config.json:   0%|          | 0.00/50.6k [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "a574760d3b814ece93f66e3762130c92",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "tokenizer.json:   0%|          | 0.00/9.09M [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "3dde60f796364c58a1e50dba4876fed9",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "special_tokens_map.json:   0%|          | 0.00/73.0 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
          ]
        }
      ],
      "source": [
        "#@title Load the Tokenizer\n",
        "\n",
        "\n",
        "from transformers import AutoTokenizer\n",
        "\n",
        "# Tokenizer\n",
        "tokenizer = AutoTokenizer.from_pretrained(model_id,\n",
        "                                          use_fast=True,\n",
        "                                          trust_remote_code=True)\n",
        "\n",
        "tokenizer.pad_token = tokenizer.eos_token\n",
        "tokenizer.pad_token_id =  tokenizer.eos_token_id\n",
        "tokenizer.padding_side = 'left'\n",
        "\n",
        "# Set a maximum length\n",
        "tokenizer.model_max_length = 512"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "1tj__2CniFm5"
      },
      "outputs": [],
      "source": [
        "#@title Quantization Parameters\n",
        "\n",
        "from transformers import BitsAndBytesConfig\n",
        "\n",
        "bnb_config = BitsAndBytesConfig(\n",
        "    load_in_4bit=True,\n",
        "    bnb_4bit_use_double_quant=True,\n",
        "    bnb_4bit_quant_type=\"nf4\",\n",
        "    bnb_4bit_compute_dtype=torch_dtype\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "YyoRd_vn3lA8"
      },
      "outputs": [],
      "source": [
        "#@title Device Map\n",
        "\n",
        "device_map = {\"\": torch.cuda.current_device()} if torch.cuda.is_available() else None"
      ]
    },
    {
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              "version_minor": 0
            },
            "text/plain": [
              "model-00004-of-00004.safetensors:   0%|          | 0.00/1.17G [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "772899524b5b409584b05bf2fa8384a9",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Loading checkpoint shards:   0%|          | 0/4 [00:00<?, ?it/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "65415f0e1860482588a7d24bf855d796",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "generation_config.json:   0%|          | 0.00/177 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "#@title Load Model\n",
        "\n",
        "from transformers import AutoModelForCausalLM\n",
        "from peft import prepare_model_for_kbit_training\n",
        "from trl import setup_chat_format\n",
        "\n",
        "model = AutoModelForCausalLM.from_pretrained(\n",
        "    model_id,\n",
        "    device_map=device_map,\n",
        "    attn_implementation=attn_implementation,\n",
        "    quantization_config=bnb_config\n",
        ")\n",
        "\n",
        "model, tokenizer = setup_chat_format(model, tokenizer)\n",
        "model = prepare_model_for_kbit_training(model)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "rn3bzMSz4PI4"
      },
      "outputs": [],
      "source": [
        "#@title LoRA Configuration\n",
        "\n",
        "from peft import LoraConfig\n",
        "\n",
        "# According to Sebastian Raschka findings\n",
        "peft_config = LoraConfig(\n",
        "        lora_alpha=128, #32\n",
        "        lora_dropout=0.05,\n",
        "        r=256,  #16\n",
        "        bias=\"none\",\n",
        "        target_modules=[\"q_proj\", \"o_proj\", \"gate_proj\", \"up_proj\",\n",
        "                        \"down_proj\", \"k_proj\", \"v_proj\"],\n",
        "        task_type=\"CAUSAL_LM\",\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "W5YJsQBs4r2P"
      },
      "outputs": [],
      "source": [
        "# @title Training Arguments\n",
        "\n",
        "from transformers import TrainingArguments\n",
        "\n",
        "# Adapted from  Phil Schmid blogpost\n",
        "args = TrainingArguments(\n",
        "    output_dir=sft_model_path,              # directory to save the model and repository id\n",
        "    num_train_epochs=2,                     # number of training epochs\n",
        "    per_device_train_batch_size=4,          # batch size per device during training\n",
        "    gradient_accumulation_steps=2,          # number of steps before performing a backward/update pass\n",
        "    gradient_checkpointing=True,            # use gradient checkpointing to save memory, use in distributed training\n",
        "    #gradient_checkpointing_kwargs={\"use_reentrant\": False}, # for more stability in distributed training, it can use more memory\n",
        "    optim=\"adamw_8bit\",                     # choose paged_adamw_8bit if noy enough memory\n",
        "    logging_steps=10,                       # log every 10 steps\n",
        "    save_strategy=\"epoch\",                  # save checkpoint every epoch\n",
        "    learning_rate=2e-4,                     # learning rate, based on QLoRA paper\n",
        "    bf16=True,                              # use bfloat16 precision\n",
        "    tf32=True,                              # use tf32 precision\n",
        "    max_grad_norm=0.3,                      # max gradient norm based on QLoRA paper\n",
        "    warmup_ratio=0.03,                      # warmup ratio based on QLoRA paper\n",
        "    lr_scheduler_type=\"constant\",           # use constant learning rate scheduler\n",
        "    push_to_hub=True,                      # push model to Hugging Face hub\n",
        "    hub_model_id=\"llama3-8b-sft-qlora-re\",\n",
        "    report_to=\"tensorboard\",               # report metrics to tensorboard\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 104,
          "referenced_widgets": [
            "2e31e0d6ac2f4114b9f4ba10369208c3",
            "bd3e7511ed4b4622aad29d01e2818475",
            "30f4b7ce81744c8190578389178e685a",
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            "06ecb6dcc86f4445912af9e56d2e507b",
            "f204fc93b7ec44e0af6cd86d9f1a52f9",
            "586c1c74d87a4e2ab549468f6f6aa082"
          ]
        },
        "id": "IMO30PnpHsAa",
        "outputId": "190012f6-b987-4e20-a807-2738b50078b4"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "2e31e0d6ac2f4114b9f4ba10369208c3",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Map:   0%|          | 0/1017 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/trl/trainer/sft_trainer.py:318: UserWarning: You passed a tokenizer with `padding_side` not equal to `right` to the SFTTrainer. This might lead to some unexpected behaviour due to overflow issues when training a model in half-precision. You might consider adding `tokenizer.padding_side = 'right'` to your code.\n",
            "  warnings.warn(\n"
          ]
        }
      ],
      "source": [
        "# @title Initialize the SFTTrainer\n",
        "\n",
        "from trl import SFTTrainer\n",
        "\n",
        "trainer = SFTTrainer(\n",
        "    model=model,\n",
        "    args=args,\n",
        "    train_dataset=train_dataset,\n",
        "    peft_config=peft_config,\n",
        "    max_seq_length=512,\n",
        "    tokenizer=tokenizer,\n",
        "    packing=False, # True if the dataset is large\n",
        "    dataset_kwargs={\n",
        "        \"add_special_tokens\": False,  # the template adds the special tokens\n",
        "        \"append_concat_token\": False, # no need to add additional separator token\n",
        "    }\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "ImceNWv-jTfJ",
        "outputId": "b9d69a23-5af6-4ab8-943f-618b892cdcda"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`.\n",
            "/usr/local/lib/python3.10/dist-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n",
            "  warnings.warn(\n",
            "The input hidden states seems to be silently casted in float32, this might be related to the fact you have upcasted embedding or layer norm layers in float32. We will cast back the input in torch.bfloat16.\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "\n",
              "    <div>\n",
              "      \n",
              "      <progress value='254' max='254' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
              "      [254/254 10:30, Epoch 1/2]\n",
              "    </div>\n",
              "    <table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              " <tr style=\"text-align: left;\">\n",
              "      <th>Step</th>\n",
              "      <th>Training Loss</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>10</td>\n",
              "      <td>1.714900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>20</td>\n",
              "      <td>0.477100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>30</td>\n",
              "      <td>0.438300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>40</td>\n",
              "      <td>0.424100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>50</td>\n",
              "      <td>0.413900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>60</td>\n",
              "      <td>0.417700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>70</td>\n",
              "      <td>0.433800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>80</td>\n",
              "      <td>0.389800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>90</td>\n",
              "      <td>0.395700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>100</td>\n",
              "      <td>0.413700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>110</td>\n",
              "      <td>0.394700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>120</td>\n",
              "      <td>0.398900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>130</td>\n",
              "      <td>0.365900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>140</td>\n",
              "      <td>0.207700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>150</td>\n",
              "      <td>0.224400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>160</td>\n",
              "      <td>0.220300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>170</td>\n",
              "      <td>0.211300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>180</td>\n",
              "      <td>0.214500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>190</td>\n",
              "      <td>0.239200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>200</td>\n",
              "      <td>0.238400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>210</td>\n",
              "      <td>0.234300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>220</td>\n",
              "      <td>0.252300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>230</td>\n",
              "      <td>0.253900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>240</td>\n",
              "      <td>0.232200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>250</td>\n",
              "      <td>0.241900</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table><p>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/peft/utils/save_and_load.py:168: UserWarning: Setting `save_embedding_layers` to `True` as the embedding layer has been resized during finetuning.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/peft/utils/save_and_load.py:168: UserWarning: Setting `save_embedding_layers` to `True` as the embedding layer has been resized during finetuning.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/peft/utils/save_and_load.py:168: UserWarning: Setting `save_embedding_layers` to `True` as the embedding layer has been resized during finetuning.\n",
            "  warnings.warn(\n"
          ]
        }
      ],
      "source": [
        "#@title Train tand Save the Model\n",
        "\n",
        "trainer.train()\n",
        "trainer.save_model()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "b2jj52sBjis7"
      },
      "outputs": [],
      "source": [
        "#@title Save Model Locally\n",
        "\n",
        "#trainer.save_model()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "L6tubmSYi23o"
      },
      "outputs": [],
      "source": [
        "#@title Clear Memory\n",
        "\n",
        "import torch\n",
        "import gc\n",
        "del model\n",
        "del tokenizer\n",
        "gc.collect()\n",
        "torch.cuda.empty_cache()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WwvWbQO8czKq"
      },
      "source": [
        "# Inference with SFT Model"
      ]
    },
    {
      "cell_type": "code",
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      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
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        },
        "id": "7s65xPFxcyTy",
        "outputId": "a02d5991-0671-4805-b901-7426421ac900"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "9bfa9a72d1fb46ca876479bd3d998563",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "adapter_config.json:   0%|          | 0.00/731 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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              "version_minor": 0
            },
            "text/plain": [
              "Loading checkpoint shards:   0%|          | 0/4 [00:00<?, ?it/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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            "text/plain": [
              "tokenizer_config.json:   0%|          | 0.00/51.2k [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
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            "text/plain": [
              "tokenizer.json:   0%|          | 0.00/9.09M [00:00<?, ?B/s]"
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          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
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              "version_minor": 0
            },
            "text/plain": [
              "special_tokens_map.json:   0%|          | 0.00/419 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
          ]
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "585565f147fd4c59b813346f3805ca0b",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "adapter_model.safetensors:   0%|          | 0.00/3.44G [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "#@title Load Peft Model\n",
        "\n",
        "from peft import AutoPeftModelForCausalLM\n",
        "from transformers import AutoTokenizer, pipeline\n",
        "import torch\n",
        "\n",
        "# HF model\n",
        "peft_model_id = \"solanaO/llama3-8b-sft-qlora-re\"\n",
        "\n",
        "# Load Model with PEFT adapter\n",
        "model = AutoPeftModelForCausalLM.from_pretrained(\n",
        "  peft_model_id,\n",
        "  device_map=\"auto\",\n",
        "  torch_dtype=torch.float16,\n",
        "  offload_buffers=True\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ODvcs3FrdGAz",
        "outputId": "754b44a2-5a22-4edf-dd55-40431ee0f487"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
          ]
        }
      ],
      "source": [
        "#@title Load Tokenizer\n",
        "\n",
        "tokenizer = AutoTokenizer.from_pretrained(peft_model_id)\n",
        "\n",
        "tokenizer.pad_token = tokenizer.eos_token\n",
        "tokenizer.pad_token_id =  tokenizer.eos_token_id\n",
        "tokenizer.padding_side = 'left'"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KInMbBY1ehVI",
        "outputId": "05b8698e-1bce-4a02-8c0a-21322edb43ea"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "The model 'PeftModelForCausalLM' is not supported for text-generation. Supported models are ['BartForCausalLM', 'BertLMHeadModel', 'BertGenerationDecoder', 'BigBirdForCausalLM', 'BigBirdPegasusForCausalLM', 'BioGptForCausalLM', 'BlenderbotForCausalLM', 'BlenderbotSmallForCausalLM', 'BloomForCausalLM', 'CamembertForCausalLM', 'LlamaForCausalLM', 'CodeGenForCausalLM', 'CohereForCausalLM', 'CpmAntForCausalLM', 'CTRLLMHeadModel', 'Data2VecTextForCausalLM', 'DbrxForCausalLM', 'ElectraForCausalLM', 'ErnieForCausalLM', 'FalconForCausalLM', 'FuyuForCausalLM', 'GemmaForCausalLM', 'GitForCausalLM', 'GPT2LMHeadModel', 'GPT2LMHeadModel', 'GPTBigCodeForCausalLM', 'GPTNeoForCausalLM', 'GPTNeoXForCausalLM', 'GPTNeoXJapaneseForCausalLM', 'GPTJForCausalLM', 'JambaForCausalLM', 'LlamaForCausalLM', 'MambaForCausalLM', 'MarianForCausalLM', 'MBartForCausalLM', 'MegaForCausalLM', 'MegatronBertForCausalLM', 'MistralForCausalLM', 'MixtralForCausalLM', 'MptForCausalLM', 'MusicgenForCausalLM', 'MusicgenMelodyForCausalLM', 'MvpForCausalLM', 'OlmoForCausalLM', 'OpenLlamaForCausalLM', 'OpenAIGPTLMHeadModel', 'OPTForCausalLM', 'PegasusForCausalLM', 'PersimmonForCausalLM', 'PhiForCausalLM', 'PLBartForCausalLM', 'ProphetNetForCausalLM', 'QDQBertLMHeadModel', 'Qwen2ForCausalLM', 'Qwen2MoeForCausalLM', 'RecurrentGemmaForCausalLM', 'ReformerModelWithLMHead', 'RemBertForCausalLM', 'RobertaForCausalLM', 'RobertaPreLayerNormForCausalLM', 'RoCBertForCausalLM', 'RoFormerForCausalLM', 'RwkvForCausalLM', 'Speech2Text2ForCausalLM', 'StableLmForCausalLM', 'Starcoder2ForCausalLM', 'TransfoXLLMHeadModel', 'TrOCRForCausalLM', 'WhisperForCausalLM', 'XGLMForCausalLM', 'XLMWithLMHeadModel', 'XLMProphetNetForCausalLM', 'XLMRobertaForCausalLM', 'XLMRobertaXLForCausalLM', 'XLNetLMHeadModel', 'XmodForCausalLM'].\n"
          ]
        }
      ],
      "source": [
        "#@title Text Generation Pipeline\n",
        "\n",
        "pipe = pipeline(\"text-generation\", model=model, tokenizer=tokenizer)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R6ekoiniJJ1e",
        "outputId": "07646c4a-0ebd-4196-db46-441448be23a3"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{'text': 'The Flash (Bartholomew Henry \"Barry\" Allen) is a superhero appearing in American comic books published by DC Comics.',\n",
              " 'gold_re': 'The Flash|is|Bartholomew Henry \"Barry\" Allen.\\nThe Flash|appears in|American comic books.\\nAmerican comic books|are published by|DC Comics.',\n",
              " 'test_re': 'The Flash|is|DC Comics.'}"
            ]
          },
          "execution_count": 98,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#@title Load the Samples Dataset\n",
        "import json\n",
        "\n",
        "with open(mini_data_path, 'rb') as f:\n",
        "\tmini_data = json.load(f)\n",
        "\n",
        "mini_data[12]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "tQmrU3a1SZis"
      },
      "outputs": [],
      "source": [
        "#@title Function to Parse to Conversational Format\n",
        "\n",
        "# Create the System Message\n",
        "\n",
        "system_message = \"\"\"You are an experienced annontator. Extract all entities and the relations between them from the following text. Write the answer as a triple entity1|relationship|entitity2. Do not add anything else.\n",
        "Example Text: Alice is from France.\n",
        "Answer: Alice|is from|France.\n",
        "\"\"\"\n",
        "\n",
        "def create_input_prompt(sample):\n",
        "    return {\n",
        "        \"messages\": [\n",
        "            {\"role\": \"system\",\"content\": system_message},\n",
        "            {\"role\": \"user\", \"content\": sample[\"text\"]},\n",
        "        ]\n",
        "    }"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 118,
          "referenced_widgets": [
            "7323f527ecc3460b8865dcd41a5662a2",
            "2376bff1bda740c79b6b4d22626ba51a",
            "9d115d661a5f42389511c180dec77510",
            "a0fd48dc5b2a458ea592c1bce6c79cd0",
            "8450095fd47c4b1fb698469ab2c35ba1",
            "082c736e481547ec8735db012b50eae9",
            "82c5282758c840678f69c1c47a43b202",
            "911736717b764e2087a876a9e59748b1",
            "a0f8e5a4b1d84b829276ee31789dafd7",
            "71a4a32314f9424e83762ab0a0ea866d",
            "8321444cbb8044d4be2658c2672fc589"
          ]
        },
        "id": "M0pZPdSQJYqi",
        "outputId": "f1b85570-3695-4627-d2ae-eaae3b63fd2f"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "7323f527ecc3460b8865dcd41a5662a2",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Map:   0%|          | 0/20 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Dataset({\n",
            "    features: ['messages'],\n",
            "    num_rows: 20\n",
            "})\n"
          ]
        }
      ],
      "source": [
        "#@title Convert Data to HuggingFace Format\n",
        "\n",
        "from datasets import Dataset\n",
        "\n",
        "test_dataset = Dataset.from_list(mini_data)\n",
        "\n",
        "# Transform to conversational format\n",
        "test_dataset = test_dataset.map(create_input_prompt,\n",
        "                      remove_columns=test_dataset.features,\n",
        "                      batched=False)\n",
        "print(test_dataset)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Sv-ZJLqyUywG"
      },
      "source": [
        "## One Sample Test"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "opWn1TeMdwNI",
        "outputId": "9e8948a9-fbd5-4f88-a200-109c9e38f85a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "<|im_start|>system\n",
            "You are an experienced annontator. Extract all entities and the relations between them from the following text. Write the answer as a triple entity1|relationship|entitity2. Do not add anything else.\n",
            "Example Text: Alice is from France.\n",
            "Answer: Alice|is from|France.\n",
            "<|im_end|>\n",
            "<|im_start|>user\n",
            "Most avalanches occur spontaneously during storms under increased load due to snowfall and/or erosion.<|im_end|>\n",
            "<|im_start|>assistant\n",
            "\n"
          ]
        }
      ],
      "source": [
        "#@title Generate the Input Prompt\n",
        "\n",
        "prompt = pipe.tokenizer.apply_chat_template(test_dataset[10][\"messages\"][:2],\n",
        "                                            tokenize=False,\n",
        "                                            add_generation_prompt=True)\n",
        "print(prompt)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "xspKp_YBdz9q"
      },
      "outputs": [],
      "source": [
        "#@title Generate the Output\n",
        "\n",
        "outputs = pipe(prompt,\n",
        "              max_new_tokens=128,\n",
        "              do_sample=True,\n",
        "              temperature=0.01,\n",
        "              top_k=50,\n",
        "              top_p=0.1,\n",
        "              )"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dLYo3IWed-2J",
        "outputId": "30e56801-140f-43ef-f323-0684377bb3d3"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Question: Most avalanches occur spontaneously during storms under increased load due to snowfall and/or erosion.\n",
            "\n",
            "Gold-RE: avalanches|occur|storms\n",
            "storms|have|snowfall\n",
            "storms|have|erosion\n",
            "avalanches|occur under|load\n",
            "load|is increased due to|snowfall\n",
            "load|is increased due to|erosion\n",
            "\n",
            "LLama3-8B-RE: Avalanches|occur spontaneously|storms.\n",
            "\n",
            "SFT-Llama3-8B-RE: avalanches|occur spontaneously during|storms.\n",
            "avalanches|occur under|increased load.\n",
            "increased load|is due to|snowfall.\n",
            "increased load|is due to|erosion.\n"
          ]
        }
      ],
      "source": [
        "#@title Display Sample Outputs\n",
        "\n",
        "print(f\"Question: {mini_data[10]['text']}\\n\")\n",
        "print(f\"Gold-RE: {mini_data[10]['gold_re']}\\n\")\n",
        "print(f\"LLama3-8B-RE: {mini_data[10]['test_re']}\\n\")\n",
        "print(f\"SFT-Llama3-8B-RE: {outputs[0]['generated_text'][len(prompt):].strip()}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NBOUzi8deFn4",
        "outputId": "63e2d569-0f97-460e-9717-b2daa9ed0480"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Processing dataset: 100%|██████████| 20/20 [01:42<00:00,  5.10s/it]\n"
          ]
        }
      ],
      "source": [
        "#@title Test on All 20 Samples\n",
        "\n",
        "from tqdm import tqdm\n",
        "\n",
        "def evaluate(sample):\n",
        "    prompt = pipe.tokenizer.apply_chat_template(sample[\"messages\"][:2],\n",
        "                                                tokenize=False,\n",
        "                                                add_generation_prompt=True)\n",
        "    outputs = pipe(prompt,\n",
        "                   max_new_tokens=128,\n",
        "                   do_sample=True,\n",
        "                   temperature=0.7,\n",
        "                   top_k=50,\n",
        "                   top_p=0.95\n",
        "                   )\n",
        "\n",
        "    predicted_answer = outputs[0]['generated_text'][len(prompt):].strip()\n",
        "    return predicted_answer\n",
        "\n",
        "\n",
        "# Iterate over test dataset and predict\n",
        "sft_generation = []\n",
        "for s in tqdm(test_dataset, desc=\"Processing dataset\"):\n",
        "    sft_generation.append(evaluate(s))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "2jr3kYPIWZo_"
      },
      "outputs": [],
      "source": [
        "#@title Combine All Test Data and Save\n",
        "import json\n",
        "\n",
        "for d, s in zip(mini_data, sft_generation):\n",
        "    d['sft_re'] = s\n",
        "\n",
        "# Data collected from the mini-test\n",
        "with open(all_tests_data, 'w') as file:\n",
        "    json.dump(mini_data, file)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "nZK9Q8lZXpSx",
        "outputId": "7764c1b3-b097-47e0-9441-96d6b637474d"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 20,\n  \"fields\": [\n    {\n      \"column\": \"text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 20,\n        \"samples\": [\n          \"There were two teams relegated last season to the 2023 J2 League.\",\n          \"California is a state in the Western United States, located along the Pacific Coast.\",\n          \"Zeus (\\u0396\\u03b5\\u03cd\\u03c2, Ze\\u00fas)\\n\\nKing of the gods, ruler of Mount Olympus, and god of the sky, weather, thunder, lightning, law, order, and justice.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"gold_re\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 20,\n        \"samples\": [\n          \"2023 J2 League|will have|two teams.\\ntwo teams|were relegated to|2023 J2 League.\\nlast season|saw relegation of|two teams.\",\n          \"California|is a|state.\\nCalifornia|is located in|Western United States.\\nCalifornia|is located along|Pacific Coast.\\nWestern United States|is in|United States.\\nPacific Coast|is in|United States.\",\n          \"Zeus|is|King of the gods\\nZeus|is|ruler of|Mount Olympus\\nZeus|is|god of|sky\\nZeus|is|god of|weather\\nZeus|is|god of|thunder\\nZeus|is|god of|lightning\\nZeus|is|god of|law\\nZeus|is|god of|order\\nZeus|is|god of|justice\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"test_re\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 20,\n        \"samples\": [\n          \"Team A|was relegated to|2023 J2 League\\nTeam B|was relegated to|2023 J2 League\",\n          \"California|is a|state\\nCalifornia|is located|Pacific Coast\\nCalifornia|is located|United States\\nUnited States|is a|country\",\n          \"Zeus|is the king of|gods.\\nZeus|is the ruler of|Mount Olympus.\\nZeus|is the god of|sky.\\nZeus|is the god of|weather.\\nZeus|is the god of|thunder.\\nZeus|is the god of|lightning.\\nZeus|is the god of|law.\\nZeus|is the god of|order.\\nZeus|is the god of|justice.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sft_re\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 20,\n        \"samples\": [\n          \"There were two teams|relegated|season\\nThere were two teams|relegated to|2023 J2 League\\n2023 J2 League|is in|season\\nseason|is in|2023\",\n          \"California|is a state in|Western United States.\\nCalifornia|is located along|Pacific Coast.\",\n          \"Zeus|is king of|gods.\\nZeus|ruler of|Mount Olympus.\\nZeus|god of|sky.\\nZeus|god of|weather.\\nZeus|god of|thunder.\\nZeus|god of|lightning.\\nZeus|god of|law.\\nZeus|god of|order.\\nZeus|god of|justice.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
              "type": "dataframe",
              "variable_name": "df"
            },
            "text/html": [
              "\n",
              "  <div id=\"df-ee754e86-9bda-48c1-b326-98f4bafdbd83\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>text</th>\n",
              "      <th>gold_re</th>\n",
              "      <th>test_re</th>\n",
              "      <th>sft_re</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>There were two teams relegated last season to the 2023 J2 League.</td>\n",
              "      <td>2023 J2 League|will have|two teams.\\ntwo teams|were relegated to|2023 J2 League.\\nlast season|saw relegation of|two teams.</td>\n",
              "      <td>Team A|was relegated to|2023 J2 League\\nTeam B|was relegated to|2023 J2 League</td>\n",
              "      <td>There were two teams|relegated|season\\nThere were two teams|relegated to|2023 J2 League\\n2023 J2 League|is in|season\\nseason|is in|2023</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>lot\\nWhilst waiting for his dinner at Pleasant's Coffee House, Hercule Poirot meets a young woman named Jennie.</td>\n",
              "      <td>Hercule Poirot|meets|Jennie.\\nHercule Poirot|waits for|dinner.\\nHercule Poirot|is at|Pleasant's Coffee House.\\nJennie|is met by|Hercule Poirot.\\nJennie|is a|young woman.</td>\n",
              "      <td>Hercule Poirot|meets|Jennie.</td>\n",
              "      <td>Hercule Poirot|meets|Jennie.\\nHercule Poirot|waits for|dinner.\\nHercule Poirot|is at|Pleasant's Coffee House.\\nJennie|is a|young woman.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Long before any knowledge of electricity existed, people were aware of shocks from electric fish.</td>\n",
              "      <td>people|were aware of|shocks\\nshocks|from|electric fish</td>\n",
              "      <td>Electric fish|were known to give|people.</td>\n",
              "      <td>people|were aware of|shocks\\nshocks|from|electric fish\\nelectric fish|had|electricity\\nelectric fish|existed in|ancient times\\nancient times|existed before|knowledge of electricity\\nknowledge of electricity|existed in|present times\\nelectric fish|existed in|present times\\nelectric fish|existed in|ancient times\\nelectric fish|existed in|present times\\nelectricity|existed in|knowledge of electricity\\nelectricity|existed in|present times\\nelectricity|existed in|ancient times\\nelectric fish|had|electric</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Indonesia, officially the Republic of Indonesia, is a country in Southeast Asia and Oceania between the Indian and Pacific oceans.</td>\n",
              "      <td>Indonesia|is a country in|Southeast Asia.\\nIndonesia|is a country in|Oceania.\\nIndonesia|is between|Indian ocean.\\nIndonesia|is between|Pacific ocean.\\nRepublic of Indonesia|is officially known as|Indonesia.</td>\n",
              "      <td>Indonesia|is|Republic of Indonesia.\\nIndonesia|is located in|Southeast Asia.\\nIndonesia|is located in|Oceania.\\nIndonesia|is between|Indian.\\nIndonesia|is between|Pacific.\\nRepublic of Indonesia|is officially|Indonesia.\\nSoutheast Asia|is located in|Indonesia.\\nOceania|is located in|Indonesia.\\nIndian|is|ocean.\\nPacific|is|ocean.</td>\n",
              "      <td>Indonesia|is|Republic of Indonesia.\\nIndonesia|is|country.\\nIndonesia|is located in|Southeast Asia.\\nIndonesia|is located in|Oceania.\\nIndonesia|is located between|Indian Ocean.\\nIndonesia|is located between|Pacific Ocean.\\nIndian Ocean|is located in|Southeast Asia.\\nPacific Ocean|is located in|Southeast Asia.\\nPacific Ocean|is located in|Oceania.\\nIndian Ocean|is located in|Oceania.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>In 1982, Nintendo developed a prototype system called the Advanced Video System (AVS).</td>\n",
              "      <td>Nintendo|developed|Advanced Video System (AVS).\\nNintendo|developed|prototype system.\\nAdvanced Video System (AVS)|is|prototype system.</td>\n",
              "      <td>Nintendo|developed|Advanced Video System</td>\n",
              "      <td>Nintendo|developed|Advanced Video System (AVS).\\nNintendo|developed|prototype system.\\nAdvanced Video System (AVS)|is a|prototype system.\\nAdvanced Video System (AVS)|was developed in|1982.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Bloomington is a city in and the county seat of Monroe County, Indiana, United States.</td>\n",
              "      <td>Bloomington|is in|Monroe County.\\nBloomington|is in|Indiana.\\nBloomington|is in|United States.\\nBloomington|is|city.\\nBloomington|is|county seat.\\nMonroe County|is in|Indiana.\\nMonroe County|is in|United States.</td>\n",
              "      <td>Bloomington|is a|city\\nBloomington|is|county seat\\nBloomington|is in|Monroe County\\nBloomington|is in|Indiana\\nBloomington|is in|United States\\nMonroe County|is|location\\nIndiana|is|location\\nUnited States|is|location</td>\n",
              "      <td>Bloomington|is a city in|Monroe County.\\nBloomington|is the county seat of|Monroe County.\\nBloomington|is in|Indiana.\\nBloomington|is in|United States.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>The Texas barrier islands are a chain of barrier islands in the Gulf of Mexico along the Texas Gulf Coast.</td>\n",
              "      <td>Texas barrier islands|are a chain of|barrier islands.\\nTexas barrier islands|are in the|Gulf of Mexico.\\nTexas barrier islands|are along the|Texas Gulf Coast.</td>\n",
              "      <td>Texas|is|barrier islands, Texas|is|chain, Texas|is|barrier islands|of, barrier islands|are|chain, barrier islands|are|in, barrier islands|are|along, Gulf of Mexico|is|in, Texas Gulf Coast|is|along.</td>\n",
              "      <td>Texas barrier islands|are a chain of barrier islands in|Gulf of Mexico.\\nTexas barrier islands|are located along|Texas Gulf Coast.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Johnson was rated among the nation's top 10 wide receivers and top 100 players by virtually every recruiting analyst.</td>\n",
              "      <td>Johnson|was rated among|the nation's top 10 wide receivers.\\nJohnson|was rated among|the nation's top 100 players.</td>\n",
              "      <td>Johnson|was rated|nation's\\nJohnson|was rated|top\\nJohnson|was rated|wide receivers\\nJohnson|was rated|top 10\\nJohnson|was rated|100\\nJohnson|was rated|players\\nanalyst|rated|Johnson</td>\n",
              "      <td>Johnson|was rated among|nation's top 10 wide receivers.\\nJohnson|was rated among|nation's top 100 players.\\nJohnson|was rated by|virtually every recruiting analyst.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>The geologic time scale is a way of representing deep time based on events that have occurred throughout Earth's history, a time span of about 4.</td>\n",
              "      <td>geologic time scale|is a way of representing|deep time.\\ndeep time|is based on|events.\\nevents|have occurred throughout|Earth's history.\\nEarth's history|has a time span of|4.</td>\n",
              "      <td>The geologic time scale|is based on|events that have occurred throughout Earth's history, Earth's history|is part of|The geologic time scale, The geologic time scale|represents|deep time, deep time|is represented by|The geologic time scale, The geologic time scale|is based on|a time span of about 4.</td>\n",
              "      <td>geologic time scale|is a|way of representing deep time.\\ngeologic time scale|is based on|events.\\nevents|have occurred|Earth's history.\\nEarth|has|history.\\nEarth's history|is|time span.\\ntime span|is about|4.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Titanic is a 1997 American epic romance and disaster film directed, written, produced, and co-edited by James Cameron.</td>\n",
              "      <td>Titanic|is|film.\\nTitanic|was directed by|James Cameron.\\nTitanic|was written by|James Cameron.\\nTitanic|was produced by|James Cameron.\\nTitanic|was co-edited by|James Cameron.\\nJames Cameron|directed|Titanic.\\nJames Cameron|wrote|Titanic.\\nJames Cameron|produced|Titanic.\\nJames Cameron|co-edited|Titanic.\\nTitanic|is|American epic romance and disaster film.</td>\n",
              "      <td>Titanic|is a|1997 American epic romance and disaster film\\nTitanic|is directed by|James Cameron\\nTitanic|is written by|James Cameron\\nTitanic|is produced by|James Cameron\\nTitanic|is co-edited by|James Cameron</td>\n",
              "      <td>Titanic|is a|1997 American epic romance and disaster film.\\nTitanic|directed by|James Cameron.\\nTitanic|written by|James Cameron.\\nTitanic|produced by|James Cameron.\\nTitanic|co-edited by|James Cameron.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Most avalanches occur spontaneously during storms under increased load due to snowfall and/or erosion.</td>\n",
              "      <td>avalanches|occur|storms\\nstorms|have|snowfall\\nstorms|have|erosion\\navalanches|occur under|load\\nload|is increased due to|snowfall\\nload|is increased due to|erosion</td>\n",
              "      <td>Avalanches|occur spontaneously|storms.</td>\n",
              "      <td>avalanches|occur|storms\\navalanches|occur|increased load\\nincreased load|is due to|snowfall\\nincreased load|is due to|erosion\\nsnowfall|is a type of|erosion\\nerosion|is a type of|avalanches\\navalanches|occur spontaneously|storms\\nstorms|have|increased load\\nincreased load|is due to|snowfall\\nincreased load|is due to|erosion\\nsnowfall|is a type of|erosion\\nerosion|is a type of|avalanches\\navalanches|occur</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Several species of shrub of the genus Coffea produce the berries from which coffee is extracted.</td>\n",
              "      <td>Coffea|is genus of|shrubs.\\nshrubs|produce|berries.\\nberries|are source of|coffee.</td>\n",
              "      <td>Coffea|produce|berries.</td>\n",
              "      <td>Coffea|is a|genus\\nCoffea|produce|berries\\nCoffea|produce|coffee\\nCoffee|is extracted from|berries\\nBerries|are produced by|Coffea\\nCoffea|has species|species1\\nCoffea|has species|species2\\nCoffea|has species|species3\\nCoffea|has species|species4\\nCoffea|has species|species5\\nCoffea|has species|species6\\nCoffea|has species|species7\\nCoffea|has species|species8\\nCoffea|</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>The Flash (Bartholomew Henry \"Barry\" Allen) is a superhero appearing in American comic books published by DC Comics.</td>\n",
              "      <td>The Flash|is|Bartholomew Henry \"Barry\" Allen.\\nThe Flash|appears in|American comic books.\\nAmerican comic books|are published by|DC Comics.</td>\n",
              "      <td>The Flash|is|DC Comics.</td>\n",
              "      <td>The Flash|is a superhero in|American comic books.\\nThe Flash|appears in|DC Comics.\\nBartholomew Henry \"Barry\" Allen|is also known as|The Flash.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Electricity generation is the process of generating electric power from sources of primary energy.</td>\n",
              "      <td>Electricity generation|is the process of generating|electric power.\\nElectricity generation|is the process of generating|primary energy.</td>\n",
              "      <td>Electricity generation|is the process of|primary energy.</td>\n",
              "      <td>Electricity generation|is|process\\nElectricity generation|is in|electricity sector\\nElectricity generation|is in|energy sector\\nElectricity generation|is in|economy\\nElectricity sector|is part of|energy sector\\nElectricity sector|is part of|economy\\nElectricity generation|involves|electric power\\nElectric power|is produced from|primary energy\\nPrimary energy|is in|energy sector\\nEnergy sector|is part of|economy\\nElectricity generation|is also known as|electricity supply\\nElectricity generation|is also known as|power generation\\nElectricity</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Angelo Moriondo, from Turin, is often erroneously credited for inventing the beverage, since he patented a steam-driven coffee beverage making device in 1884 (No.</td>\n",
              "      <td>Angelo Moriondo|is from|Turin.\\nAngelo Moriondo|patented|steam-driven coffee beverage making device.\\nAngelo Moriondo|invented in|1884.</td>\n",
              "      <td>Angelo Moriondo|is from|Turin.</td>\n",
              "      <td>Angelo Moriondo|is from|Turin.\\nAngelo Moriondo|patented|steam-driven coffee beverage making device.\\nAngelo Moriondo|patented|1884.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Zeus (Ζεύς, Zeús)\\n\\nKing of the gods, ruler of Mount Olympus, and god of the sky, weather, thunder, lightning, law, order, and justice.</td>\n",
              "      <td>Zeus|is|King of the gods\\nZeus|is|ruler of|Mount Olympus\\nZeus|is|god of|sky\\nZeus|is|god of|weather\\nZeus|is|god of|thunder\\nZeus|is|god of|lightning\\nZeus|is|god of|law\\nZeus|is|god of|order\\nZeus|is|god of|justice</td>\n",
              "      <td>Zeus|is the king of|gods.\\nZeus|is the ruler of|Mount Olympus.\\nZeus|is the god of|sky.\\nZeus|is the god of|weather.\\nZeus|is the god of|thunder.\\nZeus|is the god of|lightning.\\nZeus|is the god of|law.\\nZeus|is the god of|order.\\nZeus|is the god of|justice.</td>\n",
              "      <td>Zeus|is king of|gods.\\nZeus|ruler of|Mount Olympus.\\nZeus|god of|sky.\\nZeus|god of|weather.\\nZeus|god of|thunder.\\nZeus|god of|lightning.\\nZeus|god of|law.\\nZeus|god of|order.\\nZeus|god of|justice.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>In probability theory and statistics, the harmonic distribution is a continuous probability distribution.</td>\n",
              "      <td>probability theory|is in|statistics.\\nharmonic distribution|is a|continuous probability distribution.\\nprobability theory|deals with|harmonic distribution.</td>\n",
              "      <td>Harmonic distribution|is a|continuous probability distribution.</td>\n",
              "      <td>probability theory|is in|statistics.\\nharmonic distribution|is a|continuous probability distribution.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>California is a state in the Western United States, located along the Pacific Coast.</td>\n",
              "      <td>California|is a|state.\\nCalifornia|is located in|Western United States.\\nCalifornia|is located along|Pacific Coast.\\nWestern United States|is in|United States.\\nPacific Coast|is in|United States.</td>\n",
              "      <td>California|is a|state\\nCalifornia|is located|Pacific Coast\\nCalifornia|is located|United States\\nUnited States|is a|country</td>\n",
              "      <td>California|is a state in|Western United States.\\nCalifornia|is located along|Pacific Coast.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Atlantis Princess is the third Korean-language studio album by South Korean singer BoA, released on May 30, 2003 by SM Entertainment.</td>\n",
              "      <td>Atlantis Princess|is the third Korean-language studio album of|BoA.\\nBoA|is|South Korean singer.\\nAtlantis Princess|was released on|May 30, 2003.\\nAtlantis Princess|was released by|SM Entertainment.</td>\n",
              "      <td>BoA|is the artist of|Atlantis Princess\\nBoA|is released by|SM Entertainment\\nBoA|is from|South Korea\\nAtlantis Princess|is released by|SM Entertainment\\nAtlantis Princess|is released on|May 30, 2003\\nAtlantis Princess|is the third Korean-language studio album by|BoA\\nSM Entertainment|is the publisher of|Atlantis Princess</td>\n",
              "      <td>Atlantis Princess|is|third Korean-language studio album.\\nAtlantis Princess|is by|BoA.\\nAtlantis Princess|is released on|May 30, 2003.\\nAtlantis Princess|is released by|SM Entertainment.\\nBoA|is a|South Korean singer.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Seattle (/siˈætəl/ (listen) see-AT-əl) is a seaport city on the West Coast of the United States.</td>\n",
              "      <td>Seattle|is a|seaport city.\\nSeattle|is located on the|West Coast.\\nSeattle|is located in the|United States.</td>\n",
              "      <td>Seattle|is|United States.\\nSeattle|is located on|West Coast.\\nSeattle|is a|seaport city.</td>\n",
              "      <td>Seattle|is a|seaport city.\\nSeattle|is on|West Coast.\\nSeattle|is in|United States.</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ee754e86-9bda-48c1-b326-98f4bafdbd83')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-ee754e86-9bda-48c1-b326-98f4bafdbd83 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-ee754e86-9bda-48c1-b326-98f4bafdbd83');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-6072cb4d-4396-44d8-a12e-5f858541181f\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-6072cb4d-4396-44d8-a12e-5f858541181f')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-6072cb4d-4396-44d8-a12e-5f858541181f button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_a3cca3b8-ad94-47f4-9182-005f226fc17e\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
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              "    </button>\n",
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              "                                                                                                                                                                  text  \\\n",
              "0                                                                                                    There were two teams relegated last season to the 2023 J2 League.   \n",
              "1                                                      lot\\nWhilst waiting for his dinner at Pleasant's Coffee House, Hercule Poirot meets a young woman named Jennie.   \n",
              "2                                                                    Long before any knowledge of electricity existed, people were aware of shocks from electric fish.   \n",
              "3                                   Indonesia, officially the Republic of Indonesia, is a country in Southeast Asia and Oceania between the Indian and Pacific oceans.   \n",
              "4                                                                               In 1982, Nintendo developed a prototype system called the Advanced Video System (AVS).   \n",
              "5                                                                               Bloomington is a city in and the county seat of Monroe County, Indiana, United States.   \n",
              "6                                                           The Texas barrier islands are a chain of barrier islands in the Gulf of Mexico along the Texas Gulf Coast.   \n",
              "7                                                Johnson was rated among the nation's top 10 wide receivers and top 100 players by virtually every recruiting analyst.   \n",
              "8                    The geologic time scale is a way of representing deep time based on events that have occurred throughout Earth's history, a time span of about 4.   \n",
              "9                                               Titanic is a 1997 American epic romance and disaster film directed, written, produced, and co-edited by James Cameron.   \n",
              "10                                                              Most avalanches occur spontaneously during storms under increased load due to snowfall and/or erosion.   \n",
              "11                                                                    Several species of shrub of the genus Coffea produce the berries from which coffee is extracted.   \n",
              "12                                                The Flash (Bartholomew Henry \"Barry\" Allen) is a superhero appearing in American comic books published by DC Comics.   \n",
              "13                                                                  Electricity generation is the process of generating electric power from sources of primary energy.   \n",
              "14  Angelo Moriondo, from Turin, is often erroneously credited for inventing the beverage, since he patented a steam-driven coffee beverage making device in 1884 (No.   \n",
              "15                            Zeus (Ζεύς, Zeús)\\n\\nKing of the gods, ruler of Mount Olympus, and god of the sky, weather, thunder, lightning, law, order, and justice.   \n",
              "16                                                           In probability theory and statistics, the harmonic distribution is a continuous probability distribution.   \n",
              "17                                                                                California is a state in the Western United States, located along the Pacific Coast.   \n",
              "18                               Atlantis Princess is the third Korean-language studio album by South Korean singer BoA, released on May 30, 2003 by SM Entertainment.   \n",
              "19                                                                    Seattle (/siˈætəl/ (listen) see-AT-əl) is a seaport city on the West Coast of the United States.   \n",
              "\n",
              "                                                                                                                                                                                                                                                                                                                                                                    gold_re  \\\n",
              "0                                                                                                                                                                                                                                                2023 J2 League|will have|two teams.\\ntwo teams|were relegated to|2023 J2 League.\\nlast season|saw relegation of|two teams.   \n",
              "1                                                                                                                                                                                                 Hercule Poirot|meets|Jennie.\\nHercule Poirot|waits for|dinner.\\nHercule Poirot|is at|Pleasant's Coffee House.\\nJennie|is met by|Hercule Poirot.\\nJennie|is a|young woman.   \n",
              "2                                                                                                                                                                                                                                                                                                                    people|were aware of|shocks\\nshocks|from|electric fish   \n",
              "3                                                                                                                                                           Indonesia|is a country in|Southeast Asia.\\nIndonesia|is a country in|Oceania.\\nIndonesia|is between|Indian ocean.\\nIndonesia|is between|Pacific ocean.\\nRepublic of Indonesia|is officially known as|Indonesia.   \n",
              "4                                                                                                                                                                                                                                   Nintendo|developed|Advanced Video System (AVS).\\nNintendo|developed|prototype system.\\nAdvanced Video System (AVS)|is|prototype system.   \n",
              "5                                                                                                                                                       Bloomington|is in|Monroe County.\\nBloomington|is in|Indiana.\\nBloomington|is in|United States.\\nBloomington|is|city.\\nBloomington|is|county seat.\\nMonroe County|is in|Indiana.\\nMonroe County|is in|United States.   \n",
              "6                                                                                                                                                                                                            Texas barrier islands|are a chain of|barrier islands.\\nTexas barrier islands|are in the|Gulf of Mexico.\\nTexas barrier islands|are along the|Texas Gulf Coast.   \n",
              "7                                                                                                                                                                                                                                                        Johnson|was rated among|the nation's top 10 wide receivers.\\nJohnson|was rated among|the nation's top 100 players.   \n",
              "8                                                                                                                                                                                           geologic time scale|is a way of representing|deep time.\\ndeep time|is based on|events.\\nevents|have occurred throughout|Earth's history.\\nEarth's history|has a time span of|4.   \n",
              "9   Titanic|is|film.\\nTitanic|was directed by|James Cameron.\\nTitanic|was written by|James Cameron.\\nTitanic|was produced by|James Cameron.\\nTitanic|was co-edited by|James Cameron.\\nJames Cameron|directed|Titanic.\\nJames Cameron|wrote|Titanic.\\nJames Cameron|produced|Titanic.\\nJames Cameron|co-edited|Titanic.\\nTitanic|is|American epic romance and disaster film.   \n",
              "10                                                                                                                                                                                                     avalanches|occur|storms\\nstorms|have|snowfall\\nstorms|have|erosion\\navalanches|occur under|load\\nload|is increased due to|snowfall\\nload|is increased due to|erosion   \n",
              "11                                                                                                                                                                                                                                                                                       Coffea|is genus of|shrubs.\\nshrubs|produce|berries.\\nberries|are source of|coffee.   \n",
              "12                                                                                                                                                                                                                              The Flash|is|Bartholomew Henry \"Barry\" Allen.\\nThe Flash|appears in|American comic books.\\nAmerican comic books|are published by|DC Comics.   \n",
              "13                                                                                                                                                                                                                                 Electricity generation|is the process of generating|electric power.\\nElectricity generation|is the process of generating|primary energy.   \n",
              "14                                                                                                                                                                                                                                  Angelo Moriondo|is from|Turin.\\nAngelo Moriondo|patented|steam-driven coffee beverage making device.\\nAngelo Moriondo|invented in|1884.   \n",
              "15                                                                                                                                                 Zeus|is|King of the gods\\nZeus|is|ruler of|Mount Olympus\\nZeus|is|god of|sky\\nZeus|is|god of|weather\\nZeus|is|god of|thunder\\nZeus|is|god of|lightning\\nZeus|is|god of|law\\nZeus|is|god of|order\\nZeus|is|god of|justice   \n",
              "16                                                                                                                                                                                                              probability theory|is in|statistics.\\nharmonic distribution|is a|continuous probability distribution.\\nprobability theory|deals with|harmonic distribution.   \n",
              "17                                                                                                                                                                      California|is a|state.\\nCalifornia|is located in|Western United States.\\nCalifornia|is located along|Pacific Coast.\\nWestern United States|is in|United States.\\nPacific Coast|is in|United States.   \n",
              "18                                                                                                                                                                   Atlantis Princess|is the third Korean-language studio album of|BoA.\\nBoA|is|South Korean singer.\\nAtlantis Princess|was released on|May 30, 2003.\\nAtlantis Princess|was released by|SM Entertainment.   \n",
              "19                                                                                                                                                                                                                                                              Seattle|is a|seaport city.\\nSeattle|is located on the|West Coast.\\nSeattle|is located in the|United States.   \n",
              "\n",
              "                                                                                                                                                                                                                                                                                                                                        test_re  \\\n",
              "0                                                                                                                                                                                                                                                                Team A|was relegated to|2023 J2 League\\nTeam B|was relegated to|2023 J2 League   \n",
              "1                                                                                                                                                                                                                                                                                                                  Hercule Poirot|meets|Jennie.   \n",
              "2                                                                                                                                                                                                                                                                                                      Electric fish|were known to give|people.   \n",
              "3   Indonesia|is|Republic of Indonesia.\\nIndonesia|is located in|Southeast Asia.\\nIndonesia|is located in|Oceania.\\nIndonesia|is between|Indian.\\nIndonesia|is between|Pacific.\\nRepublic of Indonesia|is officially|Indonesia.\\nSoutheast Asia|is located in|Indonesia.\\nOceania|is located in|Indonesia.\\nIndian|is|ocean.\\nPacific|is|ocean.   \n",
              "4                                                                                                                                                                                                                                                                                                      Nintendo|developed|Advanced Video System   \n",
              "5                                                                                                                     Bloomington|is a|city\\nBloomington|is|county seat\\nBloomington|is in|Monroe County\\nBloomington|is in|Indiana\\nBloomington|is in|United States\\nMonroe County|is|location\\nIndiana|is|location\\nUnited States|is|location   \n",
              "6                                                                                                                                         Texas|is|barrier islands, Texas|is|chain, Texas|is|barrier islands|of, barrier islands|are|chain, barrier islands|are|in, barrier islands|are|along, Gulf of Mexico|is|in, Texas Gulf Coast|is|along.   \n",
              "7                                                                                                                                                        Johnson|was rated|nation's\\nJohnson|was rated|top\\nJohnson|was rated|wide receivers\\nJohnson|was rated|top 10\\nJohnson|was rated|100\\nJohnson|was rated|players\\nanalyst|rated|Johnson   \n",
              "8                                  The geologic time scale|is based on|events that have occurred throughout Earth's history, Earth's history|is part of|The geologic time scale, The geologic time scale|represents|deep time, deep time|is represented by|The geologic time scale, The geologic time scale|is based on|a time span of about 4.   \n",
              "9                                                                                                                             Titanic|is a|1997 American epic romance and disaster film\\nTitanic|is directed by|James Cameron\\nTitanic|is written by|James Cameron\\nTitanic|is produced by|James Cameron\\nTitanic|is co-edited by|James Cameron   \n",
              "10                                                                                                                                                                                                                                                                                                       Avalanches|occur spontaneously|storms.   \n",
              "11                                                                                                                                                                                                                                                                                                                      Coffea|produce|berries.   \n",
              "12                                                                                                                                                                                                                                                                                                                      The Flash|is|DC Comics.   \n",
              "13                                                                                                                                                                                                                                                                                     Electricity generation|is the process of|primary energy.   \n",
              "14                                                                                                                                                                                                                                                                                                               Angelo Moriondo|is from|Turin.   \n",
              "15                                                                            Zeus|is the king of|gods.\\nZeus|is the ruler of|Mount Olympus.\\nZeus|is the god of|sky.\\nZeus|is the god of|weather.\\nZeus|is the god of|thunder.\\nZeus|is the god of|lightning.\\nZeus|is the god of|law.\\nZeus|is the god of|order.\\nZeus|is the god of|justice.   \n",
              "16                                                                                                                                                                                                                                                                              Harmonic distribution|is a|continuous probability distribution.   \n",
              "17                                                                                                                                                                                                                  California|is a|state\\nCalifornia|is located|Pacific Coast\\nCalifornia|is located|United States\\nUnited States|is a|country   \n",
              "18           BoA|is the artist of|Atlantis Princess\\nBoA|is released by|SM Entertainment\\nBoA|is from|South Korea\\nAtlantis Princess|is released by|SM Entertainment\\nAtlantis Princess|is released on|May 30, 2003\\nAtlantis Princess|is the third Korean-language studio album by|BoA\\nSM Entertainment|is the publisher of|Atlantis Princess   \n",
              "19                                                                                                                                                                                                                                                     Seattle|is|United States.\\nSeattle|is located on|West Coast.\\nSeattle|is a|seaport city.   \n",
              "\n",
              "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               sft_re  \n",
              "0                                                                                                                                                                                                                                                                                                                                                                                                                             There were two teams|relegated|season\\nThere were two teams|relegated to|2023 J2 League\\n2023 J2 League|is in|season\\nseason|is in|2023  \n",
              "1                                                                                                                                                                                                                                                                                                                                                                                                                             Hercule Poirot|meets|Jennie.\\nHercule Poirot|waits for|dinner.\\nHercule Poirot|is at|Pleasant's Coffee House.\\nJennie|is a|young woman.  \n",
              "2                                            people|were aware of|shocks\\nshocks|from|electric fish\\nelectric fish|had|electricity\\nelectric fish|existed in|ancient times\\nancient times|existed before|knowledge of electricity\\nknowledge of electricity|existed in|present times\\nelectric fish|existed in|present times\\nelectric fish|existed in|ancient times\\nelectric fish|existed in|present times\\nelectricity|existed in|knowledge of electricity\\nelectricity|existed in|present times\\nelectricity|existed in|ancient times\\nelectric fish|had|electric  \n",
              "3                                                                                                                                                                  Indonesia|is|Republic of Indonesia.\\nIndonesia|is|country.\\nIndonesia|is located in|Southeast Asia.\\nIndonesia|is located in|Oceania.\\nIndonesia|is located between|Indian Ocean.\\nIndonesia|is located between|Pacific Ocean.\\nIndian Ocean|is located in|Southeast Asia.\\nPacific Ocean|is located in|Southeast Asia.\\nPacific Ocean|is located in|Oceania.\\nIndian Ocean|is located in|Oceania.  \n",
              "4                                                                                                                                                                                                                                                                                                                                                                       Nintendo|developed|Advanced Video System (AVS).\\nNintendo|developed|prototype system.\\nAdvanced Video System (AVS)|is a|prototype system.\\nAdvanced Video System (AVS)|was developed in|1982.  \n",
              "5                                                                                                                                                                                                                                                                                                                                                                                                             Bloomington|is a city in|Monroe County.\\nBloomington|is the county seat of|Monroe County.\\nBloomington|is in|Indiana.\\nBloomington|is in|United States.  \n",
              "6                                                                                                                                                                                                                                                                                                                                                                                                                                  Texas barrier islands|are a chain of barrier islands in|Gulf of Mexico.\\nTexas barrier islands|are located along|Texas Gulf Coast.  \n",
              "7                                                                                                                                                                                                                                                                                                                                                                                                Johnson|was rated among|nation's top 10 wide receivers.\\nJohnson|was rated among|nation's top 100 players.\\nJohnson|was rated by|virtually every recruiting analyst.  \n",
              "8                                                                                                                                                                                                                                                                                                                                                   geologic time scale|is a|way of representing deep time.\\ngeologic time scale|is based on|events.\\nevents|have occurred|Earth's history.\\nEarth|has|history.\\nEarth's history|is|time span.\\ntime span|is about|4.  \n",
              "9                                                                                                                                                                                                                                                                                                                                                          Titanic|is a|1997 American epic romance and disaster film.\\nTitanic|directed by|James Cameron.\\nTitanic|written by|James Cameron.\\nTitanic|produced by|James Cameron.\\nTitanic|co-edited by|James Cameron.  \n",
              "10                                                                                                                                            avalanches|occur|storms\\navalanches|occur|increased load\\nincreased load|is due to|snowfall\\nincreased load|is due to|erosion\\nsnowfall|is a type of|erosion\\nerosion|is a type of|avalanches\\navalanches|occur spontaneously|storms\\nstorms|have|increased load\\nincreased load|is due to|snowfall\\nincreased load|is due to|erosion\\nsnowfall|is a type of|erosion\\nerosion|is a type of|avalanches\\navalanches|occur  \n",
              "11                                                                                                                                                                                Coffea|is a|genus\\nCoffea|produce|berries\\nCoffea|produce|coffee\\nCoffee|is extracted from|berries\\nBerries|are produced by|Coffea\\nCoffea|has species|species1\\nCoffea|has species|species2\\nCoffea|has species|species3\\nCoffea|has species|species4\\nCoffea|has species|species5\\nCoffea|has species|species6\\nCoffea|has species|species7\\nCoffea|has species|species8\\nCoffea|  \n",
              "12                                                                                                                                                                                                                                                                                                                                                                                                                    The Flash|is a superhero in|American comic books.\\nThe Flash|appears in|DC Comics.\\nBartholomew Henry \"Barry\" Allen|is also known as|The Flash.  \n",
              "13  Electricity generation|is|process\\nElectricity generation|is in|electricity sector\\nElectricity generation|is in|energy sector\\nElectricity generation|is in|economy\\nElectricity sector|is part of|energy sector\\nElectricity sector|is part of|economy\\nElectricity generation|involves|electric power\\nElectric power|is produced from|primary energy\\nPrimary energy|is in|energy sector\\nEnergy sector|is part of|economy\\nElectricity generation|is also known as|electricity supply\\nElectricity generation|is also known as|power generation\\nElectricity  \n",
              "14                                                                                                                                                                                                                                                                                                                                                                                                                               Angelo Moriondo|is from|Turin.\\nAngelo Moriondo|patented|steam-driven coffee beverage making device.\\nAngelo Moriondo|patented|1884.  \n",
              "15                                                                                                                                                                                                                                                                                                                                                              Zeus|is king of|gods.\\nZeus|ruler of|Mount Olympus.\\nZeus|god of|sky.\\nZeus|god of|weather.\\nZeus|god of|thunder.\\nZeus|god of|lightning.\\nZeus|god of|law.\\nZeus|god of|order.\\nZeus|god of|justice.  \n",
              "16                                                                                                                                                                                                                                                                                                                                                                                                                                                              probability theory|is in|statistics.\\nharmonic distribution|is a|continuous probability distribution.  \n",
              "17                                                                                                                                                                                                                                                                                                                                                                                                                                                                        California|is a state in|Western United States.\\nCalifornia|is located along|Pacific Coast.  \n",
              "18                                                                                                                                                                                                                                                                                                                                          Atlantis Princess|is|third Korean-language studio album.\\nAtlantis Princess|is by|BoA.\\nAtlantis Princess|is released on|May 30, 2003.\\nAtlantis Princess|is released by|SM Entertainment.\\nBoA|is a|South Korean singer.  \n",
              "19                                                                                                                                                                                                                                                                                                                                                                                                                                                                                Seattle|is a|seaport city.\\nSeattle|is on|West Coast.\\nSeattle|is in|United States.  "
            ]
          },
          "execution_count": 106,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#@title Display the Tests Results\n",
        "\n",
        "import pandas as pd\n",
        "pd.set_option('display.max_colwidth', None)\n",
        "\n",
        "df = pd.DataFrame(mini_data)\n",
        "df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "RwUmZo6sXhXh"
      },
      "outputs": [],
      "source": []
    }
  ],
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